Artificial intelligence

Artificial intelligence

Overview
Artificial intelligence (AI) is the intelligence
Intelligence
Intelligence has been defined in different ways, including the abilities for abstract thought, understanding, communication, reasoning, learning, planning, emotional intelligence and problem solving....

 of machines and the branch of computer science
Computer science
Computer science or computing science is the study of the theoretical foundations of information and computation and of practical techniques for their implementation and application in computer systems...

 that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent
Intelligent agent
In artificial intelligence, an intelligent agent is an autonomous entity which observes through sensors and acts upon an environment using actuators and directs its activity towards achieving goals . Intelligent agents may also learn or use knowledge to achieve their goals...

 is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy
John McCarthy (computer scientist)
John McCarthy was an American computer scientist and cognitive scientist. He coined the term "artificial intelligence" , invented the Lisp programming language and was highly influential in the early development of AI.McCarthy also influenced other areas of computing such as time sharing systems...

, who coined the term in 1956, defines it as "the science and engineering of making intelligent machines."
The field was founded on the claim that a central property of humans, intelligence—the sapience of Homo sapiens—can be so precisely described that it can be simulated by a machine.
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Encyclopedia
Artificial intelligence (AI) is the intelligence
Intelligence
Intelligence has been defined in different ways, including the abilities for abstract thought, understanding, communication, reasoning, learning, planning, emotional intelligence and problem solving....

 of machines and the branch of computer science
Computer science
Computer science or computing science is the study of the theoretical foundations of information and computation and of practical techniques for their implementation and application in computer systems...

 that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent
Intelligent agent
In artificial intelligence, an intelligent agent is an autonomous entity which observes through sensors and acts upon an environment using actuators and directs its activity towards achieving goals . Intelligent agents may also learn or use knowledge to achieve their goals...

 is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy
John McCarthy (computer scientist)
John McCarthy was an American computer scientist and cognitive scientist. He coined the term "artificial intelligence" , invented the Lisp programming language and was highly influential in the early development of AI.McCarthy also influenced other areas of computing such as time sharing systems...

, who coined the term in 1956, defines it as "the science and engineering of making intelligent machines."
The field was founded on the claim that a central property of humans, intelligence—the sapience of Homo sapiens—can be so precisely described that it can be simulated by a machine. This raises philosophical issues about the nature of the mind
Mind
The concept of mind is understood in many different ways by many different traditions, ranging from panpsychism and animism to traditional and organized religious views, as well as secular and materialist philosophies. Most agree that minds are constituted by conscious experience and intelligent...

 and the ethics of creating artificial beings, issues which have been addressed by myth, fiction
Artificial intelligence in fiction
Artificial intelligence is a common topic in science fiction, whether it is in literature, film, television or theatre. Science fiction sometimes focuses on the dangers of artificial intelligence, and sometimes on its positive potential.- Myths :...

 and philosophy since antiquity. Artificial intelligence has been the subject of optimism, but has also suffered setbacks and, today, has become an essential part of the technology industry, providing the heavy lifting for many of the most difficult problems in computer science.
AI research is highly technical and specialized, deeply divided into subfields that often fail in the task of communicating with each other. Subfields have grown up around particular institutions, the work of individual researchers, the solution of specific problems, longstanding differences of opinion about how AI should be done and the application of widely differing tools. The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects. General intelligence (or "strong AI
Strong AI
Strong AI is artificial intelligence that matches or exceeds human intelligence — the intelligence of a machine that can successfully perform any intellectual task that a human being can. It is a primary goal of artificial intelligence research and an important topic for science fiction writers and...

") is still among the field's long term goals.

History


Thinking machines and artificial beings appear in Greek myths, such as Talos
Talos
In Greek mythology, Talos or Talon was a giant man of bronze who protected Europa in Crete from pirates and invaders by circling the island's shores three times daily while guarding it.- History :...

 of Crete
Crete
Crete is the largest and most populous of the Greek islands, the fifth largest island in the Mediterranean Sea, and one of the thirteen administrative regions of Greece. It forms a significant part of the economy and cultural heritage of Greece while retaining its own local cultural traits...

, the bronze robot of Hephaestus
Hephaestus
Hephaestus was a Greek god whose Roman equivalent was Vulcan. He is the son of Zeus and Hera, the King and Queen of the Gods - or else, according to some accounts, of Hera alone. He was the god of technology, blacksmiths, craftsmen, artisans, sculptors, metals, metallurgy, fire and volcanoes...

, and Pygmalion's
Pygmalion (mythology)
Pygmalion is a legendary figure of Cyprus. Though Pygmalion is the Greek version of the Phoenician royal name Pumayyaton, he is most familiar from Ovid's Metamorphoses, X, in which Pygmalion was a sculptor who fell in love with a statue he had carved.-In Ovid:In Ovid's narrative, Pygmalion was a...

 Galatea
Galatea (mythology)
-Name "Galatea":Though the name "Galatea" has become so firmly associated with Pygmalion's statue as to seem antique, its use in connection with Pygmalion originated with a post-classical writer. No extant ancient text mentions the statue's name...

. Human likenesses believed to have intelligence were built in every major civilization: animated cult image
Cult image
In the practice of religion, a cult image is a human-made object that is venerated for the deity, spirit or daemon that it embodies or represents...

s were worshipped in Egypt
Egypt
Egypt , officially the Arab Republic of Egypt, Arabic: , is a country mainly in North Africa, with the Sinai Peninsula forming a land bridge in Southwest Asia. Egypt is thus a transcontinental country, and a major power in Africa, the Mediterranean Basin, the Middle East and the Muslim world...

 and Greece
Greece
Greece , officially the Hellenic Republic , and historically Hellas or the Republic of Greece in English, is a country in southeastern Europe....

 and humanoid automaton
Automaton
An automaton is a self-operating machine. The word is sometimes used to describe a robot, more specifically an autonomous robot. An alternative spelling, now obsolete, is automation.-Etymology:...

s were built by Yan Shi, Hero of Alexandria
Hero of Alexandria
Hero of Alexandria was an ancient Greek mathematician and engineerEnc. Britannica 2007, "Heron of Alexandria" who was active in his native city of Alexandria, Roman Egypt...

 and Al-Jazari
Al-Jazari
Abū al-'Iz Ibn Ismā'īl ibn al-Razāz al-Jazarī was a Muslim polymath: a scholar, inventor, mechanical engineer, craftsman, artist, mathematician and astronomer from Al-Jazira, Mesopotamia, who lived during the Islamic Golden Age...

. It was also widely believed that artificial beings had been created by Jābir ibn Hayyān, Judah Loew and Paracelsus
Paracelsus
Paracelsus was a German-Swiss Renaissance physician, botanist, alchemist, astrologer, and general occultist....

. By the 19th and 20th centuries, artificial beings had become a common feature in fiction, as in Mary Shelley
Mary Shelley
Mary Shelley was a British novelist, short story writer, dramatist, essayist, biographer, and travel writer, best known for her Gothic novel Frankenstein: or, The Modern Prometheus . She also edited and promoted the works of her husband, the Romantic poet and philosopher Percy Bysshe Shelley...

's Frankenstein
Frankenstein
Frankenstein; or, The Modern Prometheus is a novel about a failed experiment that produced a monster, written by Mary Shelley, with inserts of poems by Percy Bysshe Shelley. Shelley started writing the story when she was eighteen, and the novel was published when she was twenty-one. The first...

or Karel Čapek
Karel Capek
Karel Čapek was Czech writer of the 20th century.-Biography:Born in 1890 in the Bohemian mountain village of Malé Svatoňovice to an overbearing, emotional mother and a distant yet adored father, Čapek was the youngest of three siblings...

's R.U.R. (Rossum's Universal Robots)
R.U.R. (Rossum's Universal Robots)
R.U.R. is a 1920 science fiction play in the Czech language by Karel Čapek. R.U.R. stands for Rossum's Universal Robots, an English phrase used as the subtitle in the Czech original. It premiered in 1921 and introduced the word "robot" to the English language and to science fiction as a whole.The...

. Pamela McCorduck
Pamela McCorduck
Pamela McCorduck is the author of a number of books concerning the history and philosophical significance of artificial intelligence, the future of engineering and the role of women and technology. She is also the author of three novels. She is a contributor to Omni, New York Times, Daedalus, the...

 argues that all of these are examples of an ancient urge, as she describes it, "to forge the gods". Stories of these creatures and their fates discuss many of the same hopes, fears and ethical concerns
Ethics of artificial intelligence
The ethics of artificial intelligence is the part of the ethics of technology specific to robots and other artificially intelligent beings. It is typically divided into roboethics, a concern with the moral behavior of humans as they design, construct, use and treat artificially intelligent beings,...

 that are presented by artificial intelligence.
Mechanical or "formal" reasoning has been developed by philosophers and mathematicians since antiquity. The study of logic led directly to the invention of the programmable digital electronic computer
Computer
A computer is a programmable machine designed to sequentially and automatically carry out a sequence of arithmetic or logical operations. The particular sequence of operations can be changed readily, allowing the computer to solve more than one kind of problem...

, based on the work of mathematician Alan Turing
Alan Turing
Alan Mathison Turing, OBE, FRS , was an English mathematician, logician, cryptanalyst, and computer scientist. He was highly influential in the development of computer science, providing a formalisation of the concepts of "algorithm" and "computation" with the Turing machine, which played a...

 and others. Turing's theory of computation
Theory of computation
In theoretical computer science, the theory of computation is the branch that deals with whether and how efficiently problems can be solved on a model of computation, using an algorithm...

 suggested that a machine, by shuffling symbols as simple as "0" and "1", could simulate any conceivable act of mathematical deduction. This, along with concurrent discoveries in neurology
Neurology
Neurology is a medical specialty dealing with disorders of the nervous system. Specifically, it deals with the diagnosis and treatment of all categories of disease involving the central, peripheral, and autonomic nervous systems, including their coverings, blood vessels, and all effector tissue,...

, information theory
Information theory
Information theory is a branch of applied mathematics and electrical engineering involving the quantification of information. Information theory was developed by Claude E. Shannon to find fundamental limits on signal processing operations such as compressing data and on reliably storing and...

 and cybernetics, inspired a small group of researchers to begin to seriously consider the possibility of building an electronic brain.
The field of AI research was founded at a conference on the campus of Dartmouth College
Dartmouth College
Dartmouth College is a private, Ivy League university in Hanover, New Hampshire, United States. The institution comprises a liberal arts college, Dartmouth Medical School, Thayer School of Engineering, and the Tuck School of Business, as well as 19 graduate programs in the arts and sciences...

 in the summer of 1956. The attendees, including John McCarthy
John McCarthy (computer scientist)
John McCarthy was an American computer scientist and cognitive scientist. He coined the term "artificial intelligence" , invented the Lisp programming language and was highly influential in the early development of AI.McCarthy also influenced other areas of computing such as time sharing systems...

, Marvin Minsky
Marvin Minsky
Marvin Lee Minsky is an American cognitive scientist in the field of artificial intelligence , co-founder of Massachusetts Institute of Technology's AI laboratory, and author of several texts on AI and philosophy.-Biography:...

, Allen Newell
Allen Newell
Allen Newell was a researcher in computer science and cognitive psychology at the RAND corporation and at Carnegie Mellon University’s School of Computer Science, Tepper School of Business, and Department of Psychology...

 and Herbert Simon
Herbert Simon
Herbert Alexander Simon was an American political scientist, economist, sociologist, and psychologist, and professor—most notably at Carnegie Mellon University—whose research ranged across the fields of cognitive psychology, cognitive science, computer science, public administration, economics,...

, became the leaders of AI research for many decades. They and their students wrote programs that were, to most people, simply astonishing: Computers were solving word problems in algebra, proving logical theorems and speaking English. By the middle of the 1960s, research in the U.S. was heavily funded by the Department of Defense and laboratories had been established around the world. AI's founders were profoundly optimistic about the future of the new field: Herbert Simon
Herbert Simon
Herbert Alexander Simon was an American political scientist, economist, sociologist, and psychologist, and professor—most notably at Carnegie Mellon University—whose research ranged across the fields of cognitive psychology, cognitive science, computer science, public administration, economics,...

 predicted that "machines will be capable, within twenty years, of doing any work a man can do" and Marvin Minsky
Marvin Minsky
Marvin Lee Minsky is an American cognitive scientist in the field of artificial intelligence , co-founder of Massachusetts Institute of Technology's AI laboratory, and author of several texts on AI and philosophy.-Biography:...

 agreed, writing that "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved".
They had failed to recognize the difficulty of some of the problems they faced. In 1974, in response to the criticism of Sir James Lighthill and ongoing pressure from the US Congress to fund more productive projects, both the U.S. and British governments cut off all undirected exploratory research in AI. The next few years, when funding for projects was hard to find, would later be called the "AI winter
AI winter
In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. The process of hype, disappointment and funding cuts are common in many emerging technologies , but the problem has been particularly acute for AI...

".
In the early 1980s, AI research was revived by the commercial success of expert systems, a form of AI program that simulated the knowledge and analytical skills of one or more human experts. By 1985 the market for AI had reached over a billion dollars. At the same time, Japan's fifth generation computer
Fifth generation computer
The Fifth Generation Computer Systems project was an initiative by Japan'sMinistry of International Trade and Industry, begun in 1982, to create a "fifth generation computer" which was supposed to perform much calculation using massive parallel processing...

 project inspired the U.S and British governments to restore funding for academic research in the field. However, beginning with the collapse of the Lisp Machine
Lisp machine
Lisp machines were general-purpose computers designed to efficiently run Lisp as their main software language. In a sense, they were the first commercial single-user workstations...

 market in 1987, AI once again fell into disrepute, and a second, longer lasting AI winter
AI winter
In the history of artificial intelligence, an AI winter is a period of reduced funding and interest in artificial intelligence research. The process of hype, disappointment and funding cuts are common in many emerging technologies , but the problem has been particularly acute for AI...

 began.
In the 1990s and early 21st century, AI achieved its greatest successes, albeit somewhat behind the scenes. Artificial intelligence is used for logistics
Logistics
Logistics is the management of the flow of goods between the point of origin and the point of destination in order to meet the requirements of customers or corporations. Logistics involves the integration of information, transportation, inventory, warehousing, material handling, and packaging, and...

, data mining
Data mining
Data mining , a relatively young and interdisciplinary field of computer science is the process of discovering new patterns from large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems...

, medical diagnosis
Medical diagnosis
Medical diagnosis refers both to the process of attempting to determine or identify a possible disease or disorder , and to the opinion reached by this process...

 and many other areas throughout the technology industry.
The success was due to several factors: the increasing computational power of computers (see Moore's law
Moore's Law
Moore's law describes a long-term trend in the history of computing hardware: the number of transistors that can be placed inexpensively on an integrated circuit doubles approximately every two years....

), a greater emphasis on solving specific subproblems, the creation of new ties between AI and other fields working on similar problems, and a new commitment by researchers to solid mathematical methods and rigorous scientific standards.

On 11 May 1997, Deep Blue became the first computer chess-playing system to beat a reigning world chess champion, Garry Kasparov
Garry Kasparov
Garry Kimovich Kasparov is a Russian chess grandmaster, a former World Chess Champion, writer, political activist, and one of the greatest chess players of all time....

. In 2005, a Stanford robot won the DARPA Grand Challenge
DARPA Grand Challenge
The DARPA Grand Challenge is a prize competition for driverless vehicles, funded by the Defense Advanced Research Projects Agency, the most prominent research organization of the United States Department of Defense...

 by driving autonomously for 131 miles along an unrehearsed desert trail.
Two years later, a team from CMU won the DARPA Urban Challenge by autonomously navigating 55 miles in an Urban environment while adhering to traffic hazards and all traffic laws. In February 2011, in a Jeopardy!
Jeopardy!
Griffin's first conception of the game used a board comprising ten categories with ten clues each, but after finding that this board could not be shown on camera easily, he reduced it to two rounds of thirty clues each, with five clues in each of six categories...

 quiz show
Quiz Show
Quiz Show is a 1994 American historical drama film produced and directed by Robert Redford. Adapted by Paul Attanasio from Richard Goodwin's memoir Remembering America, the film is based upon the Twenty One quiz show scandal of the 1950s...

 exhibition match, IBM
IBM
International Business Machines Corporation or IBM is an American multinational technology and consulting corporation headquartered in Armonk, New York, United States. IBM manufactures and sells computer hardware and software, and it offers infrastructure, hosting and consulting services in areas...

's question answering system, Watson
Watson (artificial intelligence software)
Watson is an artificial intelligence computer system capable of answering questions posed in natural language, developed in IBM's DeepQA project by a research team led by principal investigator David Ferrucci. Watson was named after IBM's first president, Thomas J...

, defeated the two greatest Jeopardy! champions, Brad Rutter
Brad Rutter
Bradford Gates "Brad" Rutter is the biggest all-time money winner on the U.S. syndicated game show Jeopardy! and the second biggest all-time money winner on a game show....

 and Ken Jennings
Ken Jennings
Kenneth Wayne "Ken" Jennings III is an American game show contestant and author. Jennings is noted for holding the record for the longest winning streak on the U.S. syndicated game show Jeopardy! and as being the all-time leading money winner on American game shows...

, by a significant margin.

The leading-edge definition of artificial intelligence research
Research
Research can be defined as the scientific search for knowledge, or as any systematic investigation, to establish novel facts, solve new or existing problems, prove new ideas, or develop new theories, usually using a scientific method...

 is changing over time. One pragmatic definition is: "AI research is that which computing scientists do not know how to do cost-effectively today." For example, in 1956 optical character recognition
Optical character recognition
Optical character recognition, usually abbreviated to OCR, is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files, to computerize a record-keeping...

 (OCR) was considered AI, but today, sophisticated OCR software with a context-sensitive spell checker
Spell checker
In computing, a spell checker is an application program that flags words in a document that may not be spelled correctly. Spell checkers may be stand-alone capable of operating on a block of text, or as part of a larger application, such as a word processor, email client, electronic dictionary,...

 and grammar checker
Grammar checker
A grammar checker in computing terms, is a program, or part of a program, that attempts to verify written text for grammatical correctness. Grammar checkers are most often implemented as a feature of a larger program, such as a word processor, but are also available as stand-alone application that...

 software comes for free with most image scanner
Image scanner
In computing, an image scanner—often abbreviated to just scanner—is a device that optically scans images, printed text, handwriting, or an object, and converts it to a digital image. Common examples found in offices are variations of the desktop scanner where the document is placed on a glass...

s. No one would any longer consider already-solved computing science problems like OCR "artificial intelligence" today.

Low-cost entertaining chess-playing software is commonly available for tablet computers. DARPA no longer provides significant funding for chess-playing computing system development. The Kinect which provides a 3D body–motion interface for the Xbox 360
Xbox 360
The Xbox 360 is the second video game console produced by Microsoft and the successor to the Xbox. The Xbox 360 competes with Sony's PlayStation 3 and Nintendo's Wii as part of the seventh generation of video game consoles...

 uses algorithms that emerged from lengthy AI research, but few consumers realize the technology source.

AI applications are no longer the exclusive domain of Department of defense R&D, but are now common place consumer items and inexpensive intelligent toys.

In common usage, the term "AI" no longer seems to apply to off-the-shelf solved computing-science problems, which may have originally emerged out of years of AI research.

Problems


"Can a machine act intelligently?
Philosophy of artificial intelligence
The philosophy of artificial intelligence attempts to answer such questions as:* Can a machine act intelligently? Can it solve any problem that a person would solve by thinking?...

" is still an open problem
Open problem
In science and mathematics, an open problem or an open question is a known problem that can be accurately stated, and has not yet been solved . Some questions remain unanswered for centuries before solutions are found...

. Taking "A machine can act intelligently" as a working hypothesis
Working hypothesis
A working hypothesis is a hypothesis that is provisionally accepted as a basis for further research in the hope that a tenable theory will be produced, even if the hypothesis ultimately fails...

, many researchers have attempted to build such a machine.

The general problem of simulating (or creating) intelligence has been broken down into a number of specific sub-problems. These consist of particular traits or capabilities that researchers would like an intelligent system to display. The traits described below have received the most attention.

Deduction, reasoning, problem solving


Early AI researchers developed algorithms that imitated the step-by-step reasoning that humans use when they solve puzzles or make logical deductions. By the late 1980s and '90s, AI research had also developed highly successful methods for dealing with uncertain
Uncertainty
Uncertainty is a term used in subtly different ways in a number of fields, including physics, philosophy, statistics, economics, finance, insurance, psychology, sociology, engineering, and information science...

 or incomplete information, employing concepts from probability
Probability
Probability is ordinarily used to describe an attitude of mind towards some proposition of whose truth we arenot certain. The proposition of interest is usually of the form "Will a specific event occur?" The attitude of mind is of the form "How certain are we that the event will occur?" The...

 and economics
Economics
Economics is the social science that analyzes the production, distribution, and consumption of goods and services. The term economics comes from the Ancient Greek from + , hence "rules of the house"...

.
For difficult problems, most of these algorithms can require enormous computational resources — most experience a "combinatorial explosion
Combinatorial explosion
In administration and computing, a combinatorial explosion is the rapidly accelerating increase in lines of communication as organizations are added in a process...

": the amount of memory or computer time required becomes astronomical when the problem goes beyond a certain size. The search for more efficient problem-solving algorithms is a high priority for AI research.

Human beings solve most of their problems using fast, intuitive judgments rather than the conscious, step-by-step deduction that early AI research was able to model. AI has made some progress at imitating this kind of "sub-symbolic" problem solving: embodied agent approaches emphasize the importance of sensorimotor skills to higher reasoning; neural net research attempts to simulate the structures inside human and animal brains that give rise to this skill.

Knowledge representation



Knowledge representation
Knowledge representation
Knowledge representation is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge...

 and knowledge engineering
Knowledge engineering
Knowledge engineering was defined in 1983 by Edward Feigenbaum, and Pamela McCorduck as follows:At present, it refers to the building, maintaining and development of knowledge-based systems...

 are central to AI research. Many of the problems machines are expected to solve will require extensive knowledge about the world. Among the things that AI needs to represent are: objects, properties, categories and relations between objects; situations, events, states and time; causes and effects; knowledge about knowledge (what we know about what other people know); and many other, less well researched domains. A representation of "what exists" is an ontology
Ontology (computer science)
In computer science and information science, an ontology formally represents knowledge as a set of concepts within a domain, and the relationships between those concepts. It can be used to reason about the entities within that domain and may be used to describe the domain.In theory, an ontology is...

 (borrowing a word from traditional philosophy
Philosophy
Philosophy is the study of general and fundamental problems, such as those connected with existence, knowledge, values, reason, mind, and language. Philosophy is distinguished from other ways of addressing such problems by its critical, generally systematic approach and its reliance on rational...

), of which the most general are called upper ontologies.

Among the most difficult problems in knowledge representation are:

Default reasoning and the qualification problem
Qualification problem
In philosophy and AI , the qualification problem is concerned with the impossibility of listing all the preconditions required for a real-world action to have its intended effect. It might be posed as how to deal with the things that prevent me from achieving my intended result...

: Many of the things people know take the form of "working assumptions." For example, if a bird comes up in conversation, people typically picture an animal that is fist sized, sings, and flies. None of these things are true about all birds. John McCarthy
John McCarthy (computer scientist)
John McCarthy was an American computer scientist and cognitive scientist. He coined the term "artificial intelligence" , invented the Lisp programming language and was highly influential in the early development of AI.McCarthy also influenced other areas of computing such as time sharing systems...

 identified this problem in 1969 as the qualification problem: for any commonsense rule that AI researchers care to represent, there tend to be a huge number of exceptions. Almost nothing is simply true or false in the way that abstract logic requires. AI research has explored a number of solutions to this problem.

The breadth of commonsense knowledge: The number of atomic facts that the average person knows is astronomical. Research projects that attempt to build a complete knowledge base of commonsense knowledge (e.g., Cyc
Cyc
Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and knowledge base of everyday common sense knowledge, with the goal of enabling AI applications to perform human-like reasoning....

) require enormous amounts of laborious ontological engineering
Ontology engineering
Ontology engineering in computer science and information science is a new field, which studies the methods and methodologies for building ontologies: formal representations of a set of concepts within a domain and the relationships between those concepts....

 — they must be built, by hand, one complicated concept at a time. A major goal is to have the computer understand enough concepts to be able to learn by reading from sources like the internet, and thus be able to add to its own ontology.

The subsymbolic form of some commonsense knowledge: Much of what people know is not represented as "facts" or "statements" that they could express verbally. For example, a chess master will avoid a particular chess position because it "feels too exposed" or an art critic can take one look at a statue and instantly realize that it is a fake. These are intuitions or tendencies that are represented in the brain non-consciously and sub-symbolically. Knowledge like this informs, supports and provides a context for symbolic, conscious knowledge. As with the related problem of sub-symbolic reasoning, it is hoped that situated AI or computational intelligence
Computational intelligence
Computational intelligence is a set of Nature-inspired computational methodologies and approaches to address complex problems of the real world applications to which traditional methodologies and approaches are ineffective or infeasible. It primarily includes Fuzzy logic systems, Neural Networks...

 will provide ways to represent this kind of knowledge.

Planning




Intelligent agents must be able to set goals and achieve them. They need a way to visualize the future (they must have a representation of the state of the world and be able to make predictions about how their actions will change it) and be able to make choices that maximize the utility
Utility
In economics, utility is a measure of customer satisfaction, referring to the total satisfaction received by a consumer from consuming a good or service....

 (or "value") of the available choices.

In classical planning problems, the agent can assume that it is the only thing acting on the world and it can be certain what the consequences of its actions may be. However, if this is not true, it must periodically check if the world matches its predictions and it must change its plan as this becomes necessary, requiring the agent to reason under uncertainty.

Multi-agent planning
Multi-agent planning
In computer science multi-agent planning involves coordinating the resources and activities of multiple "agents".NASA says, "multiagent planning is concerned with planning by multiple agents...

 uses the cooperation
Cooperation
Cooperation or co-operation is the process of working or acting together. In its simplest form it involves things working in harmony, side by side, while in its more complicated forms, it can involve something as complex as the inner workings of a human being or even the social patterns of a...

 and competition
Competition
Competition is a contest between individuals, groups, animals, etc. for territory, a niche, or a location of resources. It arises whenever two and only two strive for a goal which cannot be shared. Competition occurs naturally between living organisms which co-exist in the same environment. For...

 of many agents to achieve a given goal. Emergent behavior such as this is used by evolutionary algorithms and swarm intelligence
Swarm intelligence
Swarm intelligence is the collective behaviour of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence...

.

Learning


Machine learning
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...

 has been central to AI research from the beginning. In 1956, at the original Dartmouth AI summer conference, Ray Solomonoff
Ray Solomonoff
Ray Solomonoff was the inventor of algorithmic probability, and founder of algorithmic information theory, He was an originator of the branch of artificial intelligence based on machine learning, prediction and probability...

 wrote a report on unsupervised probabilistic machine learning: "An Inductive Inference Machine".
Unsupervised learning
Unsupervised learning
In machine learning, unsupervised learning refers to the problem of trying to find hidden structure in unlabeled data. Since the examples given to the learner are unlabeled, there is no error or reward signal to evaluate a potential solution...

 is the ability to find patterns in a stream of input. Supervised learning
Supervised learning
Supervised learning is the machine learning task of inferring a function from supervised training data. The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object and a desired output value...

 includes both classification and numerical regression
Regression analysis
In statistics, regression analysis includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables...

. Classification is used to determine what category something belongs in, after seeing a number of examples of things from several categories. Regression is the attempt to produce a function that describes the relationship between inputs and outputs and predicts how the outputs should change as the inputs change. In reinforcement learning
Reinforcement learning
Inspired by behaviorist psychology, reinforcement learning is an area of machine learning in computer science, concerned with how an agent ought to take actions in an environment so as to maximize some notion of cumulative reward...

 the agent is rewarded for good responses and punished for bad ones. These can be analyzed in terms of decision theory
Decision theory
Decision theory in economics, psychology, philosophy, mathematics, and statistics is concerned with identifying the values, uncertainties and other issues relevant in a given decision, its rationality, and the resulting optimal decision...

, using concepts like utility. The mathematical analysis of machine learning algorithms and their performance is a branch of theoretical computer science
Theoretical computer science
Theoretical computer science is a division or subset of general computer science and mathematics which focuses on more abstract or mathematical aspects of computing....

 known as computational learning theory
Computational learning theory
In theoretical computer science, computational learning theory is a mathematical field related to the analysis of machine learning algorithms.-Overview:Theoretical results in machine learning mainly deal with a type of...

.

Natural language processing



Natural language processing
Natural language processing
Natural language processing is a field of computer science and linguistics concerned with the interactions between computers and human languages; it began as a branch of artificial intelligence....

 gives machines the ability to read and understand the languages that humans speak. Many researchers hope that a sufficiently powerful natural language processing system would be able to acquire knowledge on its own, by reading the existing text available over the internet. Some straightforward applications of natural language processing include information retrieval
Information retrieval
Information retrieval is the area of study concerned with searching for documents, for information within documents, and for metadata about documents, as well as that of searching structured storage, relational databases, and the World Wide Web...

 (or text mining
Text mining
Text mining, sometimes alternately referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as...

) and machine translation
Machine translation
Machine translation, sometimes referred to by the abbreviation MT is a sub-field of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another.On a basic...

.

Motion and manipulation


The field of robotics
Robotics
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots...

 is closely related to AI. Intelligence is required for robots to be able to handle such tasks as object manipulation and navigation
Motion planning
Motion planning is a term used in robotics for the process of detailing a task into discrete motions....

, with sub-problems of localization (knowing where you are), mapping
Robotic mapping
Robotic mapping is related to cartography. The goal for an autonomous robot to be able to construct a map or floor plan and to localize itself in it...

 (learning what is around you) and motion planning
Motion planning
Motion planning is a term used in robotics for the process of detailing a task into discrete motions....

 (figuring out how to get there).

Perception


Machine perception
Machine perception
In computing, machine perception is the ability of computing machines to sense and interpret images, sounds, or other contents of their environments, or of the contents of stored media....

 is the ability to use input from sensors (such as cameras, microphones, sonar and others more exotic) to deduce aspects of the world. Computer vision
Computer vision
Computer vision is a field that includes methods for acquiring, processing, analysing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions...

 is the ability to analyze visual input. A few selected subproblems are speech recognition
Speech recognition
Speech recognition converts spoken words to text. The term "voice recognition" is sometimes used to refer to recognition systems that must be trained to a particular speaker—as is the case for most desktop recognition software...

, facial recognition
Facial recognition system
A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source...

 and object recognition
Object recognition
Object recognition in computer vision is the task of finding a given object in an image or video sequence. Humans recognize a multitude of objects in images with little effort, despite the fact that the image of the objects may vary somewhat in different view points, in many different sizes / scale...

.

Social intelligence





Emotion and social skills play two roles for an intelligent agent. First, it must be able to predict the actions of others, by understanding their motives and emotional states. (This involves elements of game theory
Game theory
Game theory is a mathematical method for analyzing calculated circumstances, such as in games, where a person’s success is based upon the choices of others...

, decision theory
Decision theory
Decision theory in economics, psychology, philosophy, mathematics, and statistics is concerned with identifying the values, uncertainties and other issues relevant in a given decision, its rationality, and the resulting optimal decision...

, as well as the ability to model human emotions and the perceptual skills to detect emotions.) Also, for good human-computer interaction, an intelligent machine also needs to display emotions. At the very least it must appear polite and sensitive to the humans it interacts with. At best, it should have normal emotions itself.

Creativity


A sub-field of AI addresses creativity
Creativity
Creativity refers to the phenomenon whereby a person creates something new that has some kind of value. What counts as "new" may be in reference to the individual creator, or to the society or domain within which the novelty occurs...

 both theoretically (from a philosophical and psychological perspective) and practically (via specific implementations of systems that generate outputs that can be considered creative, or systems that identify and assess creativity). A related area of computational research is Artificial intuition
Artificial intuition
Artificial intuition is the capacity for an artifice to function with intuition, a machine-based system that has some capacity to function analogous to human intuition.-Comparison:...

 and Artificial imagination
Artificial Imagination
Artificial imagination , also called Synthetic imagination or machine imagination is defined as artificial simulation of human imagination by general or special purpose computers or artificial neural networks....

.

General intelligence


Most researchers hope that their work will eventually be incorporated into a machine with general intelligence (known as strong AI
Strong AI
Strong AI is artificial intelligence that matches or exceeds human intelligence — the intelligence of a machine that can successfully perform any intellectual task that a human being can. It is a primary goal of artificial intelligence research and an important topic for science fiction writers and...

), combining all the skills above and exceeding human abilities at most or all of them. A few believe that anthropomorphic features like artificial consciousness
Artificial consciousness
Artificial consciousness , also known as machine consciousness or synthetic consciousness, is a field related to artificial intelligence and cognitive robotics whose aim is to define that which would have to be synthesized were consciousness to be found in an engineered artifact .Neuroscience...

 or an artificial brain
Artificial brain
Artificial brain is a term commonly used in the media to describe research that aims to develop software and hardware with cognitive abilities similar to the animal or human brain...

 may be required for such a project.

Many of the problems above are considered AI-complete
AI-complete
In the field of artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational problems is equivalent to solving the central artificial intelligence problem—making computers as intelligent as people, or strong...

: to solve one problem, you must solve them all. For example, even a straightforward, specific task like machine translation
Machine translation
Machine translation, sometimes referred to by the abbreviation MT is a sub-field of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another.On a basic...

 requires that the machine follow the author's argument (reason), know what is being talked about (knowledge), and faithfully reproduce the author's intention (social intelligence). Machine translation
Machine translation
Machine translation, sometimes referred to by the abbreviation MT is a sub-field of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another.On a basic...

, therefore, is believed to be AI-complete: it may require strong AI
Strong AI
Strong AI is artificial intelligence that matches or exceeds human intelligence — the intelligence of a machine that can successfully perform any intellectual task that a human being can. It is a primary goal of artificial intelligence research and an important topic for science fiction writers and...

 to be done as well as humans can do it.

Approaches


There is no established unifying theory or paradigm
Paradigm
The word paradigm has been used in science to describe distinct concepts. It comes from Greek "παράδειγμα" , "pattern, example, sample" from the verb "παραδείκνυμι" , "exhibit, represent, expose" and that from "παρά" , "beside, beyond" + "δείκνυμι" , "to show, to point out".The original Greek...

 that guides AI research. Researchers disagree about many issues. A few of the most long standing questions that have remained unanswered are these: should artificial intelligence simulate natural intelligence by studying psychology
Psychology
Psychology is the study of the mind and behavior. Its immediate goal is to understand individuals and groups by both establishing general principles and researching specific cases. For many, the ultimate goal of psychology is to benefit society...

 or neurology
Neurology
Neurology is a medical specialty dealing with disorders of the nervous system. Specifically, it deals with the diagnosis and treatment of all categories of disease involving the central, peripheral, and autonomic nervous systems, including their coverings, blood vessels, and all effector tissue,...

? Or is human biology as irrelevant to AI research as bird biology is to aeronautical engineering?
Can intelligent behavior be described using simple, elegant principles (such as logic
Logic
In philosophy, Logic is the formal systematic study of the principles of valid inference and correct reasoning. Logic is used in most intellectual activities, but is studied primarily in the disciplines of philosophy, mathematics, semantics, and computer science...

 or optimization
Optimization (mathematics)
In mathematics, computational science, or management science, mathematical optimization refers to the selection of a best element from some set of available alternatives....

)? Or does it necessarily require solving a large number of completely unrelated problems?
Can intelligence be reproduced using high-level symbols, similar to words and ideas? Or does it require "sub-symbolic" processing?
John Haugeland, who coined the term GOFAI (Good Old-Fashioned Artificial Intelligence), also proposed that AI should more properly be referred to as synthetic intelligence
Synthetic intelligence
Synthetic intelligence is an alternative term for artificial intelligence which emphasizes that the intelligence of machines need not be an imitation or any way artificial; it can be a genuine form of intelligence. John Haugeland proposes an analogy with artificial and synthetic diamonds—only the...

, a term which has since been adopted by some non-GOFAI researchers.

Cybernetics and brain simulation




In the 1940s and 1950s, a number of researchers explored the connection between neurology
Neurology
Neurology is a medical specialty dealing with disorders of the nervous system. Specifically, it deals with the diagnosis and treatment of all categories of disease involving the central, peripheral, and autonomic nervous systems, including their coverings, blood vessels, and all effector tissue,...

, information theory
Information theory
Information theory is a branch of applied mathematics and electrical engineering involving the quantification of information. Information theory was developed by Claude E. Shannon to find fundamental limits on signal processing operations such as compressing data and on reliably storing and...

, and cybernetics
Cybernetics
Cybernetics is the interdisciplinary study of the structure of regulatory systems. Cybernetics is closely related to information theory, control theory and systems theory, at least in its first-order form...

. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter's turtles
Turtle (robot)
Turtles are a class of educational robots designed originally in the late 1940s and used in computer science and mechanical engineering training. These devices are traditionally built low to the ground with a roughly hemispheric shell and a power train capable of a very small turning radius...

 and the Johns Hopkins Beast
Johns Hopkins Beast
The Johns Hopkins Beast was an early robot built in the 1960s at the Johns Hopkins University Applied Physics Laboratory. The machine had a rudimentary intelligence and the ability to survive on its own. As it wandered through the white halls of the laboratory, it would seek black wall outlets....

. Many of these researchers gathered for meetings of the Teleological Society at Princeton University
Princeton University
Princeton University is a private research university located in Princeton, New Jersey, United States. The school is one of the eight universities of the Ivy League, and is one of the nine Colonial Colleges founded before the American Revolution....

 and the Ratio Club
Ratio Club
The Ratio Club was a small informal dining club of young psychologists, physiologists, mathematicians and engineers who met to discuss issues in cybernetics....

 in England. By 1960, this approach was largely abandoned, although elements of it would be revived in the 1980s.

Symbolic



When access to digital computers became possible in the middle 1950s, AI research began to explore the possibility that human intelligence could be reduced to symbol manipulation. The research was centered in three institutions: CMU
Carnegie Mellon University
Carnegie Mellon University is a private research university in Pittsburgh, Pennsylvania, United States....

, Stanford and MIT, and each one developed its own style of research. John Haugeland
John Haugeland
John Haugeland was a professor of philosophy at the University of Chicago from 1999 until his death. He was chair of the philosophy department from 2004-2007. He spent at most of his career teaching at the University of Pittsburgh...

 named these approaches to AI "good old fashioned AI" or "GOFAI
GOFAI
In artificial intelligence research, GOFAI describes the oldest original approach to achieving artificial intelligence, based on logic and problem solving...

".

Cognitive simulation: Economist
Economist
An economist is a professional in the social science discipline of economics. The individual may also study, develop, and apply theories and concepts from economics and write about economic policy...

 Herbert Simon
Herbert Simon
Herbert Alexander Simon was an American political scientist, economist, sociologist, and psychologist, and professor—most notably at Carnegie Mellon University—whose research ranged across the fields of cognitive psychology, cognitive science, computer science, public administration, economics,...

 and Allen Newell
Allen Newell
Allen Newell was a researcher in computer science and cognitive psychology at the RAND corporation and at Carnegie Mellon University’s School of Computer Science, Tepper School of Business, and Department of Psychology...

 studied human problem-solving skills and attempted to formalize them, and their work laid the foundations of the field of artificial intelligence, as well as cognitive science
Cognitive science
Cognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...

, operations research
Operations research
Operations research is an interdisciplinary mathematical science that focuses on the effective use of technology by organizations...

 and management science. Their research team used the results of psychological
Psychology
Psychology is the study of the mind and behavior. Its immediate goal is to understand individuals and groups by both establishing general principles and researching specific cases. For many, the ultimate goal of psychology is to benefit society...

 experiments to develop programs that simulated the techniques that people used to solve problems. This tradition, centered at Carnegie Mellon University
Carnegie Mellon University
Carnegie Mellon University is a private research university in Pittsburgh, Pennsylvania, United States....

 would eventually culminate in the development of the Soar
Soar (cognitive architecture)
Soar is a symbolic cognitive architecture, created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University, now maintained by John Laird's research group at the University of Michigan. It is both a view of what cognition is and an implementation of that view through a...

 architecture in the middle 80s.

Logic-based: Unlike Newell
Allen Newell
Allen Newell was a researcher in computer science and cognitive psychology at the RAND corporation and at Carnegie Mellon University’s School of Computer Science, Tepper School of Business, and Department of Psychology...

 and Simon
Herbert Simon
Herbert Alexander Simon was an American political scientist, economist, sociologist, and psychologist, and professor—most notably at Carnegie Mellon University—whose research ranged across the fields of cognitive psychology, cognitive science, computer science, public administration, economics,...

, John McCarthy
John McCarthy (computer scientist)
John McCarthy was an American computer scientist and cognitive scientist. He coined the term "artificial intelligence" , invented the Lisp programming language and was highly influential in the early development of AI.McCarthy also influenced other areas of computing such as time sharing systems...

 felt that machines did not need to simulate human thought, but should instead try to find the essence of abstract reasoning and problem solving, regardless of whether people used the same algorithms. His laboratory at Stanford
Stanford University
The Leland Stanford Junior University, commonly referred to as Stanford University or Stanford, is a private research university on an campus located near Palo Alto, California. It is situated in the northwestern Santa Clara Valley on the San Francisco Peninsula, approximately northwest of San...

 (SAIL) focused on using formal logic
Logic
In philosophy, Logic is the formal systematic study of the principles of valid inference and correct reasoning. Logic is used in most intellectual activities, but is studied primarily in the disciplines of philosophy, mathematics, semantics, and computer science...

 to solve a wide variety of problems, including knowledge representation
Knowledge representation
Knowledge representation is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge...

, planning
Automated planning and scheduling
Automated planning and scheduling is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are...

 and learning
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...

. Logic was also focus of the work at the University of Edinburgh
University of Edinburgh
The University of Edinburgh, founded in 1583, is a public research university located in Edinburgh, the capital of Scotland, and a UNESCO World Heritage Site. The university is deeply embedded in the fabric of the city, with many of the buildings in the historic Old Town belonging to the university...

 and elsewhere in Europe which led to the development of the programming language Prolog
Prolog
Prolog is a general purpose logic programming language associated with artificial intelligence and computational linguistics.Prolog has its roots in first-order logic, a formal logic, and unlike many other programming languages, Prolog is declarative: the program logic is expressed in terms of...

 and the science of logic programming
Logic programming
Logic programming is, in its broadest sense, the use of mathematical logic for computer programming. In this view of logic programming, which can be traced at least as far back as John McCarthy's [1958] advice-taker proposal, logic is used as a purely declarative representation language, and a...

.

"Anti-logic" or "scruffy": Researchers at MIT (such as Marvin Minsky
Marvin Minsky
Marvin Lee Minsky is an American cognitive scientist in the field of artificial intelligence , co-founder of Massachusetts Institute of Technology's AI laboratory, and author of several texts on AI and philosophy.-Biography:...

 and Seymour Papert
Seymour Papert
Seymour Papert is an MIT mathematician, computer scientist, and educator. He is one of the pioneers of artificial intelligence, as well as an inventor of the Logo programming language....

) found that solving difficult problems in vision
Computer vision
Computer vision is a field that includes methods for acquiring, processing, analysing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions...

 and natural language processing
Natural language processing
Natural language processing is a field of computer science and linguistics concerned with the interactions between computers and human languages; it began as a branch of artificial intelligence....

 required ad-hoc solutions – they argued that there was no simple and general principle (like logic
Logic
In philosophy, Logic is the formal systematic study of the principles of valid inference and correct reasoning. Logic is used in most intellectual activities, but is studied primarily in the disciplines of philosophy, mathematics, semantics, and computer science...

) that would capture all the aspects of intelligent behavior. Roger Schank
Roger Schank
Roger Schank is an American artificial intelligence theorist, cognitive psychologist, learning scientist, educational reformer, and entrepreneur.-Academic career:...

 described their "anti-logic" approaches as "scruffy
Neats vs. scruffies
Neat and scruffy are labels for two different types of artificial intelligence research. Neats consider that solutions should be elegant, clear and provably correct...

" (as opposed to the "neat
Neats vs. scruffies
Neat and scruffy are labels for two different types of artificial intelligence research. Neats consider that solutions should be elegant, clear and provably correct...

" paradigms at CMU
Carnegie Mellon University
Carnegie Mellon University is a private research university in Pittsburgh, Pennsylvania, United States....

 and Stanford). Commonsense knowledge bases
Commonsense knowledge bases
In artificial intelligence research, commonsense knowledge is the collection of facts and information that an ordinary person is expected to know...

 (such as Doug Lenat's Cyc
Cyc
Cyc is an artificial intelligence project that attempts to assemble a comprehensive ontology and knowledge base of everyday common sense knowledge, with the goal of enabling AI applications to perform human-like reasoning....

) are an example of "scruffy" AI, since they must be built by hand, one complicated concept at a time.

Knowledge-based: When computers with large memories became available around 1970, researchers from all three traditions began to build knowledge
Knowledge representation
Knowledge representation is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge...

 into AI applications. This "knowledge revolution" led to the development and deployment of expert system
Expert system
In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning about knowledge, like an expert, and not by following the procedure of a developer as is the case in...

s (introduced by Edward Feigenbaum
Edward Feigenbaum
Edward Albert Feigenbaum is a computer scientist working in the field of artificial intelligence. He is often called the "father of expert systems."...

), the first truly successful form of AI software. The knowledge revolution was also driven by the realization that enormous amounts of knowledge would be required by many simple AI applications.

Sub-symbolic


During the 1960s, symbolic approaches had achieved great success at simulating high-level thinking in small demonstration programs. Approaches based on cybernetics
Cybernetics
Cybernetics is the interdisciplinary study of the structure of regulatory systems. Cybernetics is closely related to information theory, control theory and systems theory, at least in its first-order form...

 or neural network
Neural network
The term neural network was traditionally used to refer to a network or circuit of biological neurons. The modern usage of the term often refers to artificial neural networks, which are composed of artificial neurons or nodes...

s were abandoned or pushed into the background. By the 1980s, however, progress in symbolic AI seemed to stall and many believed that symbolic systems would never be able to imitate all the processes of human cognition, especially perception
Machine perception
In computing, machine perception is the ability of computing machines to sense and interpret images, sounds, or other contents of their environments, or of the contents of stored media....

, robotics
Robotics
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots...

, learning
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...

 and pattern recognition
Pattern recognition
In machine learning, pattern recognition is the assignment of some sort of output value to a given input value , according to some specific algorithm. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes...

. A number of researchers began to look into "sub-symbolic" approaches to specific AI problems.

Bottom-up, embodied, situated
Situated
In artificial intelligence and cognitive science, the term situated refers to an agent which is embedded in an environment. The term situated is commonly used to refer to robots, but some researchers argue that software agents can also be situated if:...

, behavior-based or nouvelle AI
Nouvelle AI
During the late 1980s, the approach now known as nouvelle AI was pioneered at the MIT Artificial Intelligence Laboratory by Rodney Brooks. Nouvelle AI is different from classical artificial intelligence in that it tries not to reach for human-level performance, but rather tries to create systems...

: Researchers from the related field of robotics
Robotics
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots...

, such as Rodney Brooks
Rodney Brooks
Rodney Allen Brooks is the former Panasonic professor of robotics at the Massachusetts Institute of Technology. Since 1986 he has authored a series of highly influential papers which have inaugurated a fundamental shift in artificial intelligence research...

, rejected symbolic AI and focused on the basic engineering problems that would allow robots to move and survive. Their work revived the non-symbolic viewpoint of the early cybernetics researchers of the 50s and reintroduced the use of control theory
Control theory
Control theory is an interdisciplinary branch of engineering and mathematics that deals with the behavior of dynamical systems. The desired output of a system is called the reference...

 in AI. This coincided with the development of the embodied mind thesis in the related field of cognitive science
Cognitive science
Cognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...

: the idea that aspects of the body (such as movement, perception and visualization) are required for higher intelligence.

Computational Intelligence: Interest in neural networks
Neural Networks
Neural Networks is the official journal of the three oldest societies dedicated to research in neural networks: International Neural Network Society, European Neural Network Society and Japanese Neural Network Society, published by Elsevier...

 and "connectionism
Connectionism
Connectionism is a set of approaches in the fields of artificial intelligence, cognitive psychology, cognitive science, neuroscience and philosophy of mind, that models mental or behavioral phenomena as the emergent processes of interconnected networks of simple units...

" was revived by David Rumelhart
David Rumelhart
David Everett Rumelhart was an American psychologist who made many contributions to the formal analysis of human cognition, working primarily within the frameworks of mathematical psychology, symbolic artificial intelligence, and parallel distributed processing...

 and others in the middle 1980s. These and other sub-symbolic approaches, such as fuzzy systems and evolutionary computation
Evolutionary computation
In computer science, evolutionary computation is a subfield of artificial intelligence that involves combinatorial optimization problems....

, are now studied collectively by the emerging discipline of computational intelligence
Computational intelligence
Computational intelligence is a set of Nature-inspired computational methodologies and approaches to address complex problems of the real world applications to which traditional methodologies and approaches are ineffective or infeasible. It primarily includes Fuzzy logic systems, Neural Networks...

.

Statistical


In the 1990s, AI researchers developed sophisticated mathematical tools to solve specific subproblems. These tools are truly scientific
Scientific method
Scientific method refers to a body of techniques for investigating phenomena, acquiring new knowledge, or correcting and integrating previous knowledge. To be termed scientific, a method of inquiry must be based on gathering empirical and measurable evidence subject to specific principles of...

, in the sense that their results are both measurable and verifiable, and they have been responsible for many of AI's recent successes. The shared mathematical language has also permitted a high level of collaboration with more established fields (like mathematics
Mathematics
Mathematics is the study of quantity, space, structure, and change. Mathematicians seek out patterns and formulate new conjectures. Mathematicians resolve the truth or falsity of conjectures by mathematical proofs, which are arguments sufficient to convince other mathematicians of their validity...

, economics
Economics
Economics is the social science that analyzes the production, distribution, and consumption of goods and services. The term economics comes from the Ancient Greek from + , hence "rules of the house"...

 or operations research
Operations research
Operations research is an interdisciplinary mathematical science that focuses on the effective use of technology by organizations...

). Stuart Russell
Stuart J. Russell
Stuart Russell is a computer scientist known for his contributions to artificial intelligence.Stuart Russell was born in Portsmouth, England. He received his Bachelor of Arts degree with first-class honours in Physics from Wadham College, Oxford in 1982, and his Ph.D. in Computer Science from...

 and Peter Norvig
Peter Norvig
Peter Norvig is an American computer scientist. He is currently the Director of Research at Google Inc.-Educational Background:...

 describe this movement as nothing less than a "revolution" and "the victory of the neats." Critiques argue that these techniques are too focussed on particular problems and have failed to address the long term goal of general intelligence.

Integrating the approaches


Intelligent agent paradigm: An intelligent agent
Intelligent agent
In artificial intelligence, an intelligent agent is an autonomous entity which observes through sensors and acts upon an environment using actuators and directs its activity towards achieving goals . Intelligent agents may also learn or use knowledge to achieve their goals...

 is a system that perceives its environment and takes actions which maximize its chances of success. The simplest intelligent agents are programs that solve specific problems. More complicated agents include human beings and organizations of human beings (such as firm
Firm
A firm is a business.Firm or The Firm may also refer to:-Organizations:* Hooligan firm, a group of unruly football fans* The Firm, Inc., a talent management company* Fair Immigration Reform Movement...

s). The paradigm gives researchers license to study isolated problems and find solutions that are both verifiable and useful, without agreeing on one single approach. An agent that solves a specific problem can use any approach that works — some agents are symbolic and logical, some are sub-symbolic neural network
Neural network
The term neural network was traditionally used to refer to a network or circuit of biological neurons. The modern usage of the term often refers to artificial neural networks, which are composed of artificial neurons or nodes...

s and others may use new approaches. The paradigm also gives researchers a common language to communicate with other fields—such as decision theory
Decision theory
Decision theory in economics, psychology, philosophy, mathematics, and statistics is concerned with identifying the values, uncertainties and other issues relevant in a given decision, its rationality, and the resulting optimal decision...

 and economics
Economics
Economics is the social science that analyzes the production, distribution, and consumption of goods and services. The term economics comes from the Ancient Greek from + , hence "rules of the house"...

—that also use concepts of abstract agents. The intelligent agent paradigm became widely accepted during the 1990s.

Agent architecture
Agent architecture
Agent architecture in computer science is a blueprint for software agents and intelligent control systems, depicting the arrangement of components...

s and cognitive architecture
Cognitive architecture
A cognitive architecture is a blueprint for intelligent agents. It proposes computational processes that act like certain cognitive systems, most often, like a person, or acts intelligent under some definition. Cognitive architectures form a subset of general agent architectures...

s: Researchers have designed systems to build intelligent systems out of interacting intelligent agents in a multi-agent system
Multi-agent system
A multi-agent system is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems that are difficult or impossible for an individual agent or a monolithic system to solve...

. A system with both symbolic and sub-symbolic components is a hybrid intelligent system
Hybrid intelligent system
Hybrid intelligent system denotes a software system which employs, in parallel, a combination of methods and techniques from artificial intelligence subfields as:* Neuro-fuzzy systems* hybrid connectionist-symbolic models* Fuzzy expert systems...

, and the study of such systems is artificial intelligence systems integration
Artificial intelligence systems integration
The core idea of A.I. systems integration is making individual software components, such as speech synthesizers, interoperable with other components, such as common sense knowledgebases, in order to create larger, broader and more capable A.I. systems...

. A hierarchical control system
Hierarchical control system
A Hierarchical control system is a form of Control System in which a set of devices and governing software is arranged in a hierarchical tree. When the links in the tree are implemented by a computer network, then that hierarchical control system is also a form of Networked control system.-...

 provides a bridge between sub-symbolic AI at its lowest, reactive levels and traditional symbolic AI at its highest levels, where relaxed time constraints permit planning and world modelling. Rodney Brooks
Rodney Brooks
Rodney Allen Brooks is the former Panasonic professor of robotics at the Massachusetts Institute of Technology. Since 1986 he has authored a series of highly influential papers which have inaugurated a fundamental shift in artificial intelligence research...

' subsumption architecture
Subsumption architecture
Subsumption architecture is a reactive robot architecture heavily associated with behavior-based robotics. The term was introduced by Rodney Brooks and colleagues in 1986...

 was an early proposal for such a hierarchical system.

Tools


In the course of 50 years of research, AI has developed a large number of tools to solve the most difficult problems in computer science
Computer science
Computer science or computing science is the study of the theoretical foundations of information and computation and of practical techniques for their implementation and application in computer systems...

. A few of the most general of these methods are discussed below.

Search and optimization


Many problems in AI can be solved in theory by intelligently searching through many possible solutions: Reasoning can be reduced to performing a search. For example, logical proof can be viewed as searching for a path that leads from premise
Premise
Premise can refer to:* Premise, a claim that is a reason for, or an objection against, some other claim as part of an argument...

s to conclusions, where each step is the application of an inference rule. Planning
Automated planning and scheduling
Automated planning and scheduling is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are...

 algorithms search through trees of goals and subgoals, attempting to find a path to a target goal, a process called means-ends analysis
Means-ends analysis
Means-Ends Analysis is a technique used in Artificial Intelligence for controlling search in problem solving computer programs.It is also a technique used at least since the 1950s as a creativity tool, most frequently mentioned in engineering books on design methods...

. Robotics
Robotics
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots...

 algorithms for moving limbs and grasping objects use local searches
Local search (optimization)
In computer science, local search is a metaheuristic method for solving computationally hard optimization problems. Local search can be used on problems that can be formulated as finding a solution maximizing a criterion among a number of candidate solutions...

 in configuration space
Configuration space
- Configuration space in physics :In classical mechanics, the configuration space is the space of possible positions that a physical system may attain, possibly subject to external constraints...

. Many learning
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...

 algorithms use search algorithms based on optimization
Optimization (mathematics)
In mathematics, computational science, or management science, mathematical optimization refers to the selection of a best element from some set of available alternatives....

.

Simple exhaustive searches are rarely sufficient for most real world problems: the search space
Search algorithm
In computer science, a search algorithm is an algorithm for finding an item with specified properties among a collection of items. The items may be stored individually as records in a database; or may be elements of a search space defined by a mathematical formula or procedure, such as the roots...

 (the number of places to search) quickly grows to astronomical numbers. The result is a search that is too slow or never completes. The solution, for many problems, is to use "heuristics" or "rules of thumb" that eliminate choices that are unlikely to lead to the goal (called "pruning
Pruning (algorithm)
Pruning is a technique in machine learning that reduces the size of decision trees by removing sections of the tree that provide little power to classify instances...

 the search tree
Search tree
In computer science, a search tree is a binary tree data structure in whose nodes data values are stored from some ordered set, in such a way that in-order traversal of the tree visits the nodes in ascending order of the stored values...

"). Heuristics supply the program with a "best guess" for the path on which the solution lies.

A very different kind of search came to prominence in the 1990s, based on the mathematical theory of optimization
Optimization (mathematics)
In mathematics, computational science, or management science, mathematical optimization refers to the selection of a best element from some set of available alternatives....

. For many problems, it is possible to begin the search with some form of a guess and then refine the guess incrementally until no more refinements can be made. These algorithms can be visualized as blind hill climbing
Hill climbing
In computer science, hill climbing is a mathematical optimization technique which belongs to the family of local search. It is an iterative algorithm that starts with an arbitrary solution to a problem, then attempts to find a better solution by incrementally changing a single element of the solution...

: we begin the search at a random point on the landscape, and then, by jumps or steps, we keep moving our guess uphill, until we reach the top. Other optimization algorithms are simulated annealing
Simulated annealing
Simulated annealing is a generic probabilistic metaheuristic for the global optimization problem of locating a good approximation to the global optimum of a given function in a large search space. It is often used when the search space is discrete...

, beam search
Beam search
In computer science, beam search is a heuristic search algorithm that explores a graph by expanding the most promising node in a limited set. Beam search is an optimization of best-first search that reduces its memory requirements...

 and random optimization
Random optimization
Random optimization is a family of numerical optimization methods that do not require the gradient of the problem to be optimized and RO can hence be used on functions that are not continuous or differentiable...

.

Evolutionary computation
Evolutionary computation
In computer science, evolutionary computation is a subfield of artificial intelligence that involves combinatorial optimization problems....

 uses a form of optimization search. For example, they may begin with a population of organisms (the guesses) and then allow them to mutate and recombine, selecting
Natural selection
Natural selection is the nonrandom process by which biologic traits become either more or less common in a population as a function of differential reproduction of their bearers. It is a key mechanism of evolution....

 only the fittest to survive each generation (refining the guesses). Forms of evolutionary computation
Evolutionary computation
In computer science, evolutionary computation is a subfield of artificial intelligence that involves combinatorial optimization problems....

 include swarm intelligence
Swarm intelligence
Swarm intelligence is the collective behaviour of decentralized, self-organized systems, natural or artificial. The concept is employed in work on artificial intelligence...

 algorithms (such as ant colony
Ant colony optimization
In computer science and operations research, the ant colony optimization algorithm ' is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs....

 or particle swarm optimization
Particle swarm optimization
In computer science, particle swarm optimization is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality...

) and evolutionary algorithms (such as genetic algorithms and genetic programming
Genetic programming
In artificial intelligence, genetic programming is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task. It is a specialization of genetic algorithms where each individual is a computer program...

).

Logic


Logic
Logic
In philosophy, Logic is the formal systematic study of the principles of valid inference and correct reasoning. Logic is used in most intellectual activities, but is studied primarily in the disciplines of philosophy, mathematics, semantics, and computer science...

 is used for knowledge representation and problem solving, but it can be applied to other problems as well. For example, the satplan
Satplan
Satplan is a method for automated planning. It converts the planning problem instance into an instance of the Boolean satisfiability problem, which is then solved using a method for establishing satisfiability such as the DPLL algorithm or WalkSAT.Given a problem instance in planning, with a given...

 algorithm uses logic for planning
Automated planning and scheduling
Automated planning and scheduling is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are...

 and inductive logic programming
Inductive logic programming
Inductive logic programming is a subfield of machine learning which uses logic programming as a uniform representation for examples, background knowledge and hypotheses...

 is a method for learning
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...

.

Several different forms of logic are used in AI research. Propositional or sentential logic is the logic of statements which can be true or false. First-order logic
First-order logic
First-order logic is a formal logical system used in mathematics, philosophy, linguistics, and computer science. It goes by many names, including: first-order predicate calculus, the lower predicate calculus, quantification theory, and predicate logic...

 also allows the use of quantifiers and predicates, and can express facts about objects, their properties, and their relations with each other. Fuzzy logic
Fuzzy logic
Fuzzy logic is a form of many-valued logic; it deals with reasoning that is approximate rather than fixed and exact. In contrast with traditional logic theory, where binary sets have two-valued logic: true or false, fuzzy logic variables may have a truth value that ranges in degree between 0 and 1...

, is a version of first-order logic which allows the truth of a statement to be represented as a value between 0 and 1, rather than simply True (1) or False (0). Fuzzy systems can be used for uncertain reasoning and have been widely used in modern industrial and consumer product control systems. Subjective logic
Subjective logic
Subjective logic is a type of probabilistic logic that explicitly takes uncertainty and belief ownership into account. In general, subjective logic is suitable for modeling and analysing situations involving uncertainty and incomplete knowledge...

 models uncertainty in a different and more explicit manner than fuzzy-logic: a given binomial opinion satisfies belief + disbelief + uncertainty = 1 within a Beta distribution. By this method, ignorance can be distinguished from probabilistic statements that an agent makes with high confidence.

Default logic
Default logic
Default logic is a non-monotonic logic proposed by Raymond Reiter to formalize reasoning with default assumptions.Default logic can express facts like “by default, something is true”; by contrast, standard logic can only express that something is true or that something is false...

s, non-monotonic logic
Non-monotonic logic
A non-monotonic logic is a formal logic whose consequence relation is not monotonic. Most studied formal logics have a monotonic consequence relation, meaning that adding a formula to a theory never produces a reduction of its set of consequences. Intuitively, monotonicity indicates that learning a...

s and circumscription are forms of logic designed to help with default reasoning and the qualification problem
Qualification problem
In philosophy and AI , the qualification problem is concerned with the impossibility of listing all the preconditions required for a real-world action to have its intended effect. It might be posed as how to deal with the things that prevent me from achieving my intended result...

. Several extensions of logic have been designed to handle specific domains of knowledge
Knowledge representation
Knowledge representation is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge...

, such as: description logic
Description logic
Description logic is a family of formal knowledge representation languages. It is more expressive than propositional logic but has more efficient decision problems than first-order predicate logic....

s; situation calculus
Situation calculus
The situation calculus is a logic formalism designed for representing and reasoning about dynamical domains. It was first introduced by John McCarthy in 1963. The main version of the situational calculus that is presented in this article is based on that introduced by Ray Reiter in 1991...

, event calculus
Event calculus
The event calculus is a logical language for representing and reasoning about actions and their effects first presented by Robert Kowalski and Marek Sergot in 1986.It was extended by Murray Shanahan and Rob Miller in the 1990s....

 and fluent calculus
Fluent calculus
The fluent calculus is a formalism for expressing dynamical domains in first-order logic. It is a variant of the situation calculus; the main difference is that situations are considered representations of states. A binary function symbol \circ is used to concatenate the terms that represent facts...

 (for representing events and time); causal calculus; belief calculus; and modal logic
Modal logic
Modal logic is a type of formal logic that extends classical propositional and predicate logic to include operators expressing modality. Modals — words that express modalities — qualify a statement. For example, the statement "John is happy" might be qualified by saying that John is...

s.

Probabilistic methods for uncertain reasoning


Many problems in AI (in reasoning, planning, learning, perception and robotics) require the agent to operate with incomplete or uncertain information. AI researchers have devised a number of powerful tools to solve these problems using methods from probability
Probability
Probability is ordinarily used to describe an attitude of mind towards some proposition of whose truth we arenot certain. The proposition of interest is usually of the form "Will a specific event occur?" The attitude of mind is of the form "How certain are we that the event will occur?" The...

 theory and economics
Economics
Economics is the social science that analyzes the production, distribution, and consumption of goods and services. The term economics comes from the Ancient Greek from + , hence "rules of the house"...

.

Bayesian network
Bayesian network
A Bayesian network, Bayes network, belief network or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph . For example, a Bayesian network could represent the probabilistic...

s are a very general tool that can be used for a large number of problems: reasoning (using the Bayesian inference
Bayesian inference
In statistics, Bayesian inference is a method of statistical inference. It is often used in science and engineering to determine model parameters, make predictions about unknown variables, and to perform model selection...

 algorithm), learning
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...

 (using the expectation-maximization algorithm
Expectation-maximization algorithm
In statistics, an expectation–maximization algorithm is an iterative method for finding maximum likelihood or maximum a posteriori estimates of parameters in statistical models, where the model depends on unobserved latent variables...

), planning
Automated planning and scheduling
Automated planning and scheduling is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are...

 (using decision networks) and perception
Machine perception
In computing, machine perception is the ability of computing machines to sense and interpret images, sounds, or other contents of their environments, or of the contents of stored media....

 (using dynamic Bayesian network
Dynamic Bayesian network
A dynamic Bayesian network is a Bayesian network that represents sequences of variables. These sequences are often time-series or sequences of symbols . The hidden Markov model can be considered as a simple dynamic Bayesian network.- References :* , Zoubin Ghahramani, Lecture Notes In Computer...

s). Probabilistic algorithms can also be used for filtering, prediction, smoothing and finding explanations for streams of data, helping perception
Machine perception
In computing, machine perception is the ability of computing machines to sense and interpret images, sounds, or other contents of their environments, or of the contents of stored media....

 systems to analyze processes that occur over time (e.g., hidden Markov model
Hidden Markov model
A hidden Markov model is a statistical Markov model in which the system being modeled is assumed to be a Markov process with unobserved states. An HMM can be considered as the simplest dynamic Bayesian network. The mathematics behind the HMM was developed by L. E...

s or Kalman filter
Kalman filter
In statistics, the Kalman filter is a mathematical method named after Rudolf E. Kálmán. Its purpose is to use measurements observed over time, containing noise and other inaccuracies, and produce values that tend to be closer to the true values of the measurements and their associated calculated...

s).

A key concept from the science of economics is "utility
Utility
In economics, utility is a measure of customer satisfaction, referring to the total satisfaction received by a consumer from consuming a good or service....

": a measure of how valuable something is to an intelligent agent. Precise mathematical tools have been developed that analyze how an agent can make choices and plan, using decision theory
Decision theory
Decision theory in economics, psychology, philosophy, mathematics, and statistics is concerned with identifying the values, uncertainties and other issues relevant in a given decision, its rationality, and the resulting optimal decision...

, decision analysis
Decision analysis
Decision analysis is the discipline comprising the philosophy, theory, methodology, and professional practice necessary to address important decisions in a formal manner...

, information value theory
Applied information economics
Applied information economics is a decision analysis method developed by Douglas W. Hubbard and partially described in his book How to Measure Anything: Finding the Value of Intangibles in Business . AIE is a method for the practical application of several proven methods from decision theory and...

. These tools include models such as Markov decision process
Markov decision process
Markov decision processes , named after Andrey Markov, provide a mathematical framework for modeling decision-making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs are useful for studying a wide range of optimization problems solved via...

es, dynamic decision networks, game theory
Game theory
Game theory is a mathematical method for analyzing calculated circumstances, such as in games, where a person’s success is based upon the choices of others...

 and mechanism design
Mechanism design
Mechanism design is a field in game theory studying solution concepts for a class of private information games...

.

Classifiers and statistical learning methods


The simplest AI applications can be divided into two types: classifiers ("if shiny then diamond") and controllers ("if shiny then pick up"). Controllers do however also classify conditions before inferring actions, and therefore classification forms a central part of many AI systems. Classifiers are functions that use pattern matching
Pattern matching
In computer science, pattern matching is the act of checking some sequence of tokens for the presence of the constituents of some pattern. In contrast to pattern recognition, the match usually has to be exact. The patterns generally have the form of either sequences or tree structures...

 to determine a closest match. They can be tuned according to examples, making them very attractive for use in AI. These examples are known as observations or patterns. In supervised learning, each pattern belongs to a certain predefined class. A class can be seen as a decision that has to be made. All the observations combined with their class labels are known as a data set. When a new observation is received, that observation is classified based on previous experience.

A classifier can be trained in various ways; there are many statistical and machine learning
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...

 approaches. The most widely used classifiers are the neural network
Artificial neural network
An artificial neural network , usually called neural network , is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes...

,
kernel methods
Kernel methods
In computer science, kernel methods are a class of algorithms for pattern analysis, whose best known elementis the support vector machine...

 such as the support vector machine
Support vector machine
A support vector machine is a concept in statistics and computer science for a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis...

,
k-nearest neighbor algorithm
K-nearest neighbor algorithm
In pattern recognition, the k-nearest neighbor algorithm is a method for classifying objects based on closest training examples in the feature space. k-NN is a type of instance-based learning, or lazy learning where the function is only approximated locally and all computation is deferred until...

,
Gaussian mixture model,
naive Bayes classifier
Naive Bayes classifier
A naive Bayes classifier is a simple probabilistic classifier based on applying Bayes' theorem with strong independence assumptions...

,
and decision tree
Decision tree learning
Decision tree learning, used in statistics, data mining and machine learning, uses a decision tree as a predictive model which maps observations about an item to conclusions about the item's target value. More descriptive names for such tree models are classification trees or regression trees...

.
The performance of these classifiers have been compared over a wide range of tasks. Classifier performance depends greatly on the characteristics of the data to be classified. There is no single classifier that works best on all given problems; this is also referred to as the "no free lunch" theorem. Determining a suitable classifier for a given problem is still more an art than science.

Neural networks



The study of artificial neural network
Artificial neural network
An artificial neural network , usually called neural network , is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes...

s began in the decade before the field AI research was founded, in the work of Walter Pitts
Walter Pitts
Walter Harry Pitts, Jr. was a logician who worked in the field of cognitive psychology.He proposed landmark theoretical formulations of neural activity and emergent processes that influenced diverse fields such as cognitive sciences and psychology, philosophy, neurosciences, computer science,...

 and Warren McCullough. Other important early researchers were Frank Rosenblatt
Frank Rosenblatt
Frank Rosenblatt was a New York City born computer scientist who completed the Perceptron, or MARK 1, computer at Cornell University in 1960...

, who invented the perceptron
Perceptron
The perceptron is a type of artificial neural network invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt. It can be seen as the simplest kind of feedforward neural network: a linear classifier.- Definition :...

 and Paul Werbos
Paul Werbos
Paul J. Werbos is a scientist best known for his 1974 Harvard University Ph.D. thesis, which first described the process of training artificial neural networks through backpropagation of errors. The thesis, and some supplementary information, can be found in his book, The Roots of Backpropagation...

 who developed the backpropagation
Backpropagation
Backpropagation is a common method of teaching artificial neural networks how to perform a given task. Arthur E. Bryson and Yu-Chi Ho described it as a multi-stage dynamic system optimization method in 1969 . It wasn't until 1974 and later, when applied in the context of neural networks and...

 algorithm.

The main categories of networks are acyclic or feedforward neural networks (where the signal passes in only one direction) and recurrent neural network
Recurrent neural network
A recurrent neural network is a class of neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process...

s (which allow feedback). Among the most popular feedforward networks are perceptron
Perceptron
The perceptron is a type of artificial neural network invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt. It can be seen as the simplest kind of feedforward neural network: a linear classifier.- Definition :...

s, multi-layer perceptrons and radial basis networks. Among recurrent networks, the most famous is the Hopfield net
Hopfield net
A Hopfield network is a form of recurrent artificial neural network invented by John Hopfield. Hopfield nets serve as content-addressable memory systems with binary threshold units. They are guaranteed to converge to a local minimum, but convergence to one of the stored patterns is not guaranteed...

, a form of attractor network, which was first described by John Hopfield in 1982. Neural networks can be applied to the problem of intelligent control
Intelligent control
Intelligent control is a class of control techniques, that use various AI computing approaches like neural networks, Bayesian probability, fuzzy logic, machine learning, evolutionary computation and genetic algorithms.- Overview :...

 (for robotics) or learning
Machine learning
Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases...

, using such techniques as Hebbian learning and competitive learning
Competitive learning
Competitive learning is a form of unsupervised learning in artificial neural networks, in which nodes compete for the right to respond to a subset of the input data. A variant of Hebbian learning, competitive learning works by increasing the specialization of each node in the network...

.

Hierarchical temporal memory
Hierarchical Temporal Memory
Hierarchical temporal memory is a machine learning model developed by Jeff Hawkins and Dileep George of Numenta, Inc. that models some of the structural and algorithmic properties of the neocortex. HTM is a biomimetic model based on the memory-prediction theory of brain function described by Jeff...

 is an approach that models some of the structural and algorithmic properties of the neocortex
Neocortex
The neocortex , also called the neopallium and isocortex , is a part of the brain of mammals. It is the outer layer of the cerebral hemispheres, and made up of six layers, labelled I to VI...

.

Control theory



Control theory
Control theory
Control theory is an interdisciplinary branch of engineering and mathematics that deals with the behavior of dynamical systems. The desired output of a system is called the reference...

, the grandchild of cybernetics
Cybernetics
Cybernetics is the interdisciplinary study of the structure of regulatory systems. Cybernetics is closely related to information theory, control theory and systems theory, at least in its first-order form...

, has many important applications, especially in robotics
Robotics
Robotics is the branch of technology that deals with the design, construction, operation, structural disposition, manufacture and application of robots...

.

Languages


AI researchers have developed several specialized languages for AI research, including Lisp
Lisp programming language
Lisp is a family of computer programming languages with a long history and a distinctive, fully parenthesized syntax. Originally specified in 1958, Lisp is the second-oldest high-level programming language in widespread use today; only Fortran is older...

 and Prolog
Prolog
Prolog is a general purpose logic programming language associated with artificial intelligence and computational linguistics.Prolog has its roots in first-order logic, a formal logic, and unlike many other programming languages, Prolog is declarative: the program logic is expressed in terms of...

.

Evaluating progress



In 1950, Alan Turing proposed a general procedure to test the intelligence of an agent now known as the Turing test
Turing test
The Turing test is a test of a machine's ability to exhibit intelligent behaviour. In Turing's original illustrative example, a human judge engages in a natural language conversation with a human and a machine designed to generate performance indistinguishable from that of a human being. All...

. This procedure allows almost all the major problems of artificial intelligence to be tested. However, it is a very difficult challenge and at present all agents fail.

Artificial intelligence can also be evaluated on specific problems such as small problems in chemistry, hand-writing recognition and game-playing. Such tests have been termed subject matter expert Turing test
Subject matter expert Turing test
A subject matter expert Turing test is a variation of the Turing test where a computer system attempts to replicate an expert in a given field such as chemistry or marketing. It is also known as a Feigenbaum test and was proposed by Edward Feigenbaum in a 2003 paper.The concept is also described...

s. Smaller problems provide more achievable goals and there are an ever-increasing number of positive results.

The broad classes of outcome for an AI test are: (1) Optimal: it is not possible to perform better. (2) Strong super-human: performs better than all humans. (3) Super-human: performs better than most humans. (4) Sub-human: performs worse than most humans. For example, performance at draughts
Draughts
Draughts is a group of abstract strategy board games between two players which involve diagonal moves of uniform pieces and mandatory captures by jumping over the enemy's pieces. Draughts developed from alquerque...

 is optimal, performance at chess is super-human and nearing strong super-human (see Computer chess#Computers versus humans) and performance at many everyday tasks (such as recognizing a face or crossing a room without bumping into something) is sub-human.

A quite different approach measures machine intelligence through tests which are developed from mathematical definitions of intelligence. Examples of these kinds of tests start in the late nineties devising intelligence tests using notions from Kolmogorov complexity
Kolmogorov complexity
In algorithmic information theory , the Kolmogorov complexity of an object, such as a piece of text, is a measure of the computational resources needed to specify the object...

 and data compression
Data compression
In computer science and information theory, data compression, source coding or bit-rate reduction is the process of encoding information using fewer bits than the original representation would use....

. Two major advantages of mathematical definitions are their applicability to nonhuman intelligences and their absence of a requirement for human testers.

Applications


Artificial intelligence techniques are pervasive and are too numerous to list. Frequently, when a technique reaches mainstream use, it is no longer considered artificial intelligence; this phenomenon is described as the AI effect
AI effect
The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by arguing that it is not real intelligence....

.

Competitions and prizes



There are a number of competitions and prizes to promote research in artificial intelligence. The main areas promoted are: general machine intelligence, conversational behavior, data-mining, driverless cars, robot soccer and games.

Platforms


A platform
Platform (computing)
A computing platform includes some sort of hardware architecture and a software framework , where the combination allows software, particularly application software, to run...

 (or "computing platform") is defined as "some sort of hardware architecture or software framework (including application frameworks), that allows software to run." As Rodney Brooks pointed out many years ago, it is not just the artificial intelligence software that defines the AI features of the platform, but rather the actual platform itself that affects the AI that results, i.e., we need to be working out AI problems on real-world platforms rather than in isolation.

A wide variety of platforms has allowed different aspects of AI to develop, ranging from expert systems, albeit PC
Personal computer
A personal computer is any general-purpose computer whose size, capabilities, and original sales price make it useful for individuals, and which is intended to be operated directly by an end-user with no intervening computer operator...

-based but still an entire real-world system, to various robot platforms such as the widely available Roomba
Roomba
The Roomba is a series of autonomous robotic vacuum cleaners sold by iRobot. Under normal operating conditions, it is able to navigate a living space and common obstacles while vacuuming the floor...

 with open interface.

Philosophy


Artificial intelligence, by claiming to be able to recreate the capabilities of the human mind
Mind
The concept of mind is understood in many different ways by many different traditions, ranging from panpsychism and animism to traditional and organized religious views, as well as secular and materialist philosophies. Most agree that minds are constituted by conscious experience and intelligent...

, is both a challenge and an inspiration for philosophy
Philosophy
Philosophy is the study of general and fundamental problems, such as those connected with existence, knowledge, values, reason, mind, and language. Philosophy is distinguished from other ways of addressing such problems by its critical, generally systematic approach and its reliance on rational...

. Are there limits to how intelligent machines can be? Is there an essential difference between human intelligence and artificial intelligence? Can a machine have a mind
Mind
The concept of mind is understood in many different ways by many different traditions, ranging from panpsychism and animism to traditional and organized religious views, as well as secular and materialist philosophies. Most agree that minds are constituted by conscious experience and intelligent...

 and consciousness
Consciousness
Consciousness is a term that refers to the relationship between the mind and the world with which it interacts. It has been defined as: subjectivity, awareness, the ability to experience or to feel, wakefulness, having a sense of selfhood, and the executive control system of the mind...

? A few of the most influential answers to these questions are given below.

Turing's "polite convention"
Computing machinery and intelligence
Computing Machinery and Intelligence, written by Alan Turing and published in 1950 in Mind, is a seminal paper on the topic of artificial intelligence in which the concept of what is now known as the Turing test was introduced to a wide audience....

: We need not decide if a machine can "think"; we need only decide if a machine can act as intelligently as a human being. This approach to the philosophical problems associated with artificial intelligence forms the basis of the Turing test
Turing test
The Turing test is a test of a machine's ability to exhibit intelligent behaviour. In Turing's original illustrative example, a human judge engages in a natural language conversation with a human and a machine designed to generate performance indistinguishable from that of a human being. All...

.

The Dartmouth proposal: "Every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it." This conjecture was printed in the proposal for the Dartmouth Conference of 1956, and represents the position of most working AI researchers.

Newell and Simon's physical symbol system hypothesis
Physical symbol system
A physical symbol system takes physical patterns , combining them into structures and manipulating them to produce new expressions....

: "A physical symbol system has the necessary and sufficient means of general intelligent action." Newell and Simon argue that intelligences consist of formal operations on symbols. Hubert Dreyfus
Hubert Dreyfus
Hubert Lederer Dreyfus is an American philosopher. He is a professor of philosophy at the University of California, Berkeley....

 argued that, on the contrary, human expertise depends on unconscious instinct rather than conscious symbol manipulation and on having a "feel" for the situation rather than explicit symbolic knowledge. (See Dreyfus' critique of AI.)

Gödel's incompleteness theorem: A formal system
Formal system
In formal logic, a formal system consists of a formal language and a set of inference rules, used to derive an expression from one or more other premises that are antecedently supposed or derived . The axioms and rules may be called a deductive apparatus...

 (such as a computer program) cannot prove all true statements. Roger Penrose
Roger Penrose
Sir Roger Penrose OM FRS is an English mathematical physicist and Emeritus Rouse Ball Professor of Mathematics at the Mathematical Institute, University of Oxford and Emeritus Fellow of Wadham College...

 is among those who claim that Gödel's theorem limits what machines can do. (See The Emperor's New Mind
The Emperor's New Mind
The Emperor's New Mind: Concerning Computers, Minds and The Laws of Physics is a 1989 book by mathematical physicist Sir Roger Penrose.Penrose presents the argument that human consciousness is non-algorithmic, and thus is not capable of being modeled by a conventional Turing machine-type of digital...

.)

Searle's strong AI hypothesis: "The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds." John Searle counters this assertion with his Chinese room
Chinese room
The Chinese room is a thought experiment by John Searle, which first appeared in his paper "Minds, Brains, and Programs", published in Behavioral and Brain Sciences in 1980...

 argument, which asks us to look inside the computer and try to find where the "mind" might be.

The artificial brain
Artificial brain
Artificial brain is a term commonly used in the media to describe research that aims to develop software and hardware with cognitive abilities similar to the animal or human brain...

 argument: The brain can be simulated. Hans Moravec
Hans Moravec
Hans Moravec is an adjunct faculty member at the Robotics Institute of Carnegie Mellon University. He is known for his work on robotics, artificial intelligence, and writings on the impact of technology. Moravec also is a futurist with many of his publications and predictions focusing on...

, Ray Kurzweil and others have argued that it is technologically feasible to copy the brain directly into hardware and software, and that such a simulation will be essentially identical to the original.

Predictions and ethics


Artificial Intelligence is a common topic in both science fiction
Science fiction
Science fiction is a genre of fiction dealing with imaginary but more or less plausible content such as future settings, futuristic science and technology, space travel, aliens, and paranormal abilities...

 and projections about the future of technology and society. The existence of an artificial intelligence that rivals human intelligence raises difficult ethical issues, and the potential power of the technology inspires both hopes and fears.
In fiction, Artificial Intelligence has appeared fulfilling many roles, including
a servant (R2D2 in Star Wars
Star Wars
Star Wars is an American epic space opera film series created by George Lucas. The first film in the series was originally released on May 25, 1977, under the title Star Wars, by 20th Century Fox, and became a worldwide pop culture phenomenon, followed by two sequels, released at three-year...

),
a law enforcer (K.I.T.T. "Knight Rider"),
a comrade (Lt. Commander Data
Data (Star Trek)
Lieutenant Commander Data is a character in the fictional Star Trek universe portrayed by actor Brent Spiner. He appears in the television series Star Trek: The Next Generation and the feature films Star Trek Generations, Star Trek: First Contact, Star Trek: Insurrection, and Star Trek...

 in Star Trek: The Next Generation
Star Trek: The Next Generation
Star Trek: The Next Generation is an American science fiction television series created by Gene Roddenberry as part of the Star Trek franchise. Roddenberry, Rick Berman, and Michael Piller served as executive producers at different times throughout the production...

),
a conqueror/overlord (The Matrix
The Matrix
The Matrix is a 1999 science fiction-action film written and directed by Larry and Andy Wachowski, starring Keanu Reeves, Laurence Fishburne, Carrie-Anne Moss, Joe Pantoliano, and Hugo Weaving...

),
a dictator (With Folded Hands
With Folded Hands
"With Folded Hands ..." is a 1947 science fiction novelette by Jack Williamson . Willamson's influence for this story was in the aftermath of World War II and the atomic bombing of Hiroshima and Nagasaki and his concern that "some of the technological creations we had developed with the best...

),
a benevolent provider/de facto ruler (The Culture
The Culture
The Culture is a fictional interstellar anarchist, socialist, and utopian society created by the Scottish writer Iain M. Banks which features in a number of science fiction novels and works of short fiction by him, collectively called the Culture series....

),
an assassin (Terminator),
a sentient race (Battlestar Galactica/Transformers
Transformers
A transformer is a device that transfers electrical energy from one circuit to another by magnetic coupling.Transformer may also refer to:* ASUS Eee Pad Transformer, an Android 3.2 Honeycomb tablet computer manufacturer by Asus...

),
an extension to human abilities (Ghost in the Shell
Ghost in the Shell
is a Japanese multimedia franchise composed of manga, animated films, anime series, video games and novels. It focuses on the activities of the counter-terrorist organization Public Security Section 9 in a futuristic, cyberpunk Japan ....

)
and the savior of the human race (R. Daneel Olivaw
R. Daneel Olivaw
R. Daneel Olivaw is a fictional robot created by Isaac Asimov. The "R" initial in his name stands for "robot," a naming convention in Asimov's future society...

 in the Asimov's Robot Series).
Mary Shelley
Mary Shelley
Mary Shelley was a British novelist, short story writer, dramatist, essayist, biographer, and travel writer, best known for her Gothic novel Frankenstein: or, The Modern Prometheus . She also edited and promoted the works of her husband, the Romantic poet and philosopher Percy Bysshe Shelley...

's Frankenstein
Frankenstein
Frankenstein; or, The Modern Prometheus is a novel about a failed experiment that produced a monster, written by Mary Shelley, with inserts of poems by Percy Bysshe Shelley. Shelley started writing the story when she was eighteen, and the novel was published when she was twenty-one. The first...

considers a key issue in the ethics of artificial intelligence
Ethics of artificial intelligence
The ethics of artificial intelligence is the part of the ethics of technology specific to robots and other artificially intelligent beings. It is typically divided into roboethics, a concern with the moral behavior of humans as they design, construct, use and treat artificially intelligent beings,...

: if a machine can be created that has intelligence, could it also feel
Sentience
Sentience is the ability to feel, perceive or be conscious, or to have subjective experiences. Eighteenth century philosophers used the concept to distinguish the ability to think from the ability to feel . In modern western philosophy, sentience is the ability to have sensations or experiences...

? If it can feel, does it have the same rights as a human? The idea also appears in modern science fiction
Science fiction
Science fiction is a genre of fiction dealing with imaginary but more or less plausible content such as future settings, futuristic science and technology, space travel, aliens, and paranormal abilities...

, including the films I Robot, Blade Runner
Blade Runner
Blade Runner is a 1982 American science fiction film directed by Ridley Scott and starring Harrison Ford, Rutger Hauer, and Sean Young. The screenplay, written by Hampton Fancher and David Peoples, is loosely based on the novel Do Androids Dream of Electric Sheep? by Philip K...

and A.I.: Artificial Intelligence, in which humanoid machines have the ability to feel human emotions. This issue, now known as "robot rights", is currently being considered by, for example, California's Institute for the Future
Institute for the Future
The Institute for the Future is a Palo Alto, California–based think tank established in 1968, as a spin-off from the RAND Corporation, to help organizations plan for the long-term future....

, although many critics believe that the discussion is premature. The subject is profoundly discussed in the 2010 documentary film Plug & Pray
Plug & Pray
Plug & Pray is a 2010 documentary film about the promise, problems and ethics of artificial intelligence and robotics. The main protagonists are the former MIT professor Joseph Weizenbaum and the futurist Raymond Kurzweil.- Synopsis :...

.
Martin Ford, author of The Lights in the Tunnel: Automation, Accelerating Technology and the Economy of the Future, and others argue that specialized artificial intelligence applications, robotics and other forms of automation will ultimately result in significant unemployment
Unemployment
Unemployment , as defined by the International Labour Organization, occurs when people are without jobs and they have actively sought work within the past four weeks...

 as machines begin to match and exceed the capability of workers to perform most routine and repetitive jobs. Ford predicts that many knowledge-based occupations—and in particular entry level jobs—will be increasingly susceptible to automation via expert systems, machine learning and other AI-enhanced applications. AI-based applications may also be used to amplify the capabilities of low-wage offshore workers, making it more feasible to outsource knowledge work.
Joseph Weizenbaum
Joseph Weizenbaum
Joseph Weizenbaum was a German-American author and professor emeritus of computer science at MIT.-Life and career:...

 wrote that AI applications can not, by definition, successfully simulate genuine human empathy and that the use of AI technology in fields such as customer service
Customer service
Customer service is the provision of service to customers before, during and after a purchase.According to Turban et al. , “Customer service is a series of activities designed to enhance the level of customer satisfaction – that is, the feeling that a product or service has met the customer...

 or psychotherapy
Psychotherapy
Psychotherapy is a general term referring to any form of therapeutic interaction or treatment contracted between a trained professional and a client or patient; family, couple or group...

 was deeply misguided. Weizenbaum was also bothered that AI researchers (and some philosophers) were willing to view the human mind as nothing more than a computer program (a position now known as computationalism). To Weizenbaum these points suggest that AI research devalues human life.
Many futurists believe that artificial intelligence will ultimately transcend the limits of progress. Ray Kurzweil has used Moore's law
Moore's Law
Moore's law describes a long-term trend in the history of computing hardware: the number of transistors that can be placed inexpensively on an integrated circuit doubles approximately every two years....

 (which describes the relentless exponential improvement in digital technology) to calculate that desktop computer
Desktop computer
A desktop computer is a personal computer in a form intended for regular use at a single location, as opposed to a mobile laptop or portable computer. Early desktop computers are designed to lay flat on the desk, while modern towers stand upright...

s will have the same processing power as human brains by the year 2029. He also predicts that by 2045 artificial intelligence will reach a point where it is able to improve itself at a rate that far exceeds anything conceivable in the past, a scenario that science fiction
Science fiction
Science fiction is a genre of fiction dealing with imaginary but more or less plausible content such as future settings, futuristic science and technology, space travel, aliens, and paranormal abilities...

 writer Vernor Vinge
Vernor Vinge
Vernor Steffen Vinge is a retired San Diego State University Professor of Mathematics, computer scientist, and science fiction author. He is best known for his Hugo Award-winning novels and novellas A Fire Upon the Deep , A Deepness in the Sky , Rainbows End , Fast Times at Fairmont High ...

 named the "singularity
Technological singularity
Technological singularity refers to the hypothetical future emergence of greater-than-human intelligence through technological means. Since the capabilities of such an intelligence would be difficult for an unaided human mind to comprehend, the occurrence of a technological singularity is seen as...

".
Robot designer Hans Moravec
Hans Moravec
Hans Moravec is an adjunct faculty member at the Robotics Institute of Carnegie Mellon University. He is known for his work on robotics, artificial intelligence, and writings on the impact of technology. Moravec also is a futurist with many of his publications and predictions focusing on...

, cyberneticist Kevin Warwick
Kevin Warwick
Kevin Warwick is a British scientist and professor of cybernetics at the University of Reading, Reading, Berkshire, United Kingdom...

 and inventor Ray Kurzweil have predicted that humans and machines will merge in the future into cyborg
Cyborg
A cyborg is a being with both biological and artificial parts. The term was coined in 1960 when Manfred Clynes and Nathan S. Kline used it in an article about the advantages of self-regulating human-machine systems in outer space. D. S...

s that are more capable and powerful than either. This idea, called transhumanism
Transhumanism
Transhumanism, often abbreviated as H+ or h+, is an international intellectual and cultural movement that affirms the possibility and desirability of fundamentally transforming the human condition by developing and making widely available technologies to eliminate aging and to greatly enhance human...

, which has roots in Aldous Huxley
Aldous Huxley
Aldous Leonard Huxley was an English writer and one of the most prominent members of the famous Huxley family. Best known for his novels including Brave New World and a wide-ranging output of essays, Huxley also edited the magazine Oxford Poetry, and published short stories, poetry, travel...

 and Robert Ettinger
Robert Ettinger
Robert Chester Wilson Ettinger was an American academic, known as "the father of cryonics" because of the impact of his 1962 book The Prospect of Immortality...

, has been illustrated in fiction as well, for example in the manga
Manga
Manga is the Japanese word for "comics" and consists of comics and print cartoons . In the West, the term "manga" has been appropriated to refer specifically to comics created in Japan, or by Japanese authors, in the Japanese language and conforming to the style developed in Japan in the late 19th...

 Ghost in the Shell
Ghost in the Shell
is a Japanese multimedia franchise composed of manga, animated films, anime series, video games and novels. It focuses on the activities of the counter-terrorist organization Public Security Section 9 in a futuristic, cyberpunk Japan ....

and the science-fiction series Dune
Dune (novel)
Dune is a science fiction novel written by Frank Herbert, published in 1965. It won the Hugo Award in 1966, and the inaugural Nebula Award for Best Novel...

.
Edward Fredkin
Edward Fredkin
Edward Fredkin is an early pioneer of digital physics. In recent work, he uses the term digital philosophy . His primary contributions include his work on reversible computing and cellular automata...

 argues that "artificial intelligence is the next stage in evolution," an idea first proposed by Samuel Butler
Samuel Butler (novelist)
Samuel Butler was an iconoclastic Victorian author who published a variety of works. Two of his most famous pieces are the Utopian satire Erewhon and a semi-autobiographical novel published posthumously, The Way of All Flesh...

's "Darwin among the Machines
Darwin Among the Machines
"Darwin among the Machines" appeared as the heading of an article published in The Press newspaper on 13 June 1863 in Christchurch, New Zealand...

" (1863), and expanded upon by George Dyson
George Dyson (science historian)
George Dyson is a scientific historian, the son of Freeman Dyson and Verena Huber-Dyson, brother of Esther Dyson, and the grandson of Sir George Dyson. He is the father of Lauren Dyson. When he was sixteen he went to live in British Columbia in Canada to pursue his interest in kayaking and...

 in his book of the same name in 1998.

Pamela McCorduck
Pamela McCorduck
Pamela McCorduck is the author of a number of books concerning the history and philosophical significance of artificial intelligence, the future of engineering and the role of women and technology. She is also the author of three novels. She is a contributor to Omni, New York Times, Daedalus, the...

 writes that all these scenarios are expressions of the ancient human desire to, as she calls it, "forge the gods".

See also


  • AI-complete
    AI-complete
    In the field of artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational problems is equivalent to solving the central artificial intelligence problem—making computers as intelligent as people, or strong...

  • Artificial intelligence in fiction
    Artificial intelligence in fiction
    Artificial intelligence is a common topic in science fiction, whether it is in literature, film, television or theatre. Science fiction sometimes focuses on the dangers of artificial intelligence, and sometimes on its positive potential.- Myths :...

  • Artificial Intelligence (journal)
    Artificial Intelligence (journal)
    Artificial Intelligence is a scientific journal on artificial intelligence research. It was established in 1970 and is published by Elsevier. The journal is abstracted and indexed in Scopus and Science Citation Index. The 2009 Impact Factor for this journal is 3.036 and the 5-Year Impact Factor is...

  • Artificial intelligence (video games)
  • Synthetic intelligence
    Synthetic intelligence
    Synthetic intelligence is an alternative term for artificial intelligence which emphasizes that the intelligence of machines need not be an imitation or any way artificial; it can be a genuine form of intelligence. John Haugeland proposes an analogy with artificial and synthetic diamonds—only the...

  • Cognitive sciences
  • Human Cognome Project
    Human Cognome Project
    The Human Cognome Project is an effort to reverse engineer the human brain by studying both its structure and function, in order to fully understand mental processes, also known as cognition. The project has many parallels to the Human Genome Project...

  • Friendly artificial intelligence
    Friendly artificial intelligence
    A Friendly Artificial Intelligence or FAI is an artificial intelligence that has a positive rather than negative effect on humanity. Friendly AI also refers to the field of knowledge required to build such an AI...

  • List of basic artificial intelligence topics

List of AI researchers
  • List of important AI publications
  • List of AI projects
  • List of emerging technologies
  • List of scientific journals
  • Philosophy of mind
    Philosophy of mind
    Philosophy of mind is a branch of philosophy that studies the nature of the mind, mental events, mental functions, mental properties, consciousness and their relationship to the physical body, particularly the brain. The mind-body problem, i.e...

  • Technological singularity
    Technological singularity
    Technological singularity refers to the hypothetical future emergence of greater-than-human intelligence through technological means. Since the capabilities of such an intelligence would be difficult for an unaided human mind to comprehend, the occurrence of a technological singularity is seen as...

  • Never-Ending Language Learning
    Never-Ending Language Learning
    Never-Ending Language Learning system is a semantic machine learning system developed by a research team at Carnegie Mellon University, and supported by grants from DARPA, Google, and the NSF, with portions of the system running on a supercomputing cluster provided by Yahoo!.-Process and...


Other sources



| publisher=ACM
| year=1998
| title=ACM Computing Classification System: Artificial intelligence
| url=http://www.acm.org/class/1998/I.2.html | accessdate=2007-08-30
}} BibTex Internet Archive....., Presidential Address to the Association for the Advancement of Artificial Intelligence
Association for the Advancement of Artificial Intelligence
The Association for the Advancement of Artificial Intelligence or AAAI is an international, nonprofit, scientific society devoted to advancing the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines...

..

Further reading

  • TechCast Article Series, John Sagi, Framing Consciousness
  • Boden, Margaret, Mind As Machine, Oxford University Press
    Oxford University Press
    Oxford University Press is the largest university press in the world. It is a department of the University of Oxford and is governed by a group of 15 academics appointed by the Vice-Chancellor known as the Delegates of the Press. They are headed by the Secretary to the Delegates, who serves as...

    , 2006
  • Johnston, John (2008) "The Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI", MIT Press
  • Myers, Courtney Boyd ed. (2009). The AI Report. Forbes June 2009
  • Sun, R. & Bookman, L. (eds.), Computational Architectures: Integrating Neural and Symbolic Processes. Kluwer Academic Publishers, Needham, MA. 1994.

External links


  • What Is AI? — An introduction to artificial intelligence by AI founder John McCarthy
    John McCarthy (computer scientist)
    John McCarthy was an American computer scientist and cognitive scientist. He coined the term "artificial intelligence" , invented the Lisp programming language and was highly influential in the early development of AI.McCarthy also influenced other areas of computing such as time sharing systems...

    .
  • AITopics — A large directory of links and other resources maintained by the Association for the Advancement of Artificial Intelligence
    Association for the Advancement of Artificial Intelligence
    The Association for the Advancement of Artificial Intelligence or AAAI is an international, nonprofit, scientific society devoted to advancing the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines...

    , the leading organization of academic AI researchers.
  • Artificial Intelligence Discussion group