R-CAST
Encyclopedia
R-CAST is a group decision support system
based on research on naturalistic decision making
. Its architecture, based on multiple software agents, supports decision-making teams by anticipating information relevant to their decisions based on a shared mental model about the context of decision making.
The R-CAST technology aims to address both of these challenges.
The R-CAST approach is based on four major concepts:
, led by Dr. John Yen
.
The R-CAST architecture is component-based and reconfigurable. By selecting components suitable for an application, R-CAST can be configured into a wide range of agents: from simple reflex agents to RPD-enabled agents. Key components of R-CAST include the RPD model interpreter, the knowledge base, the information manager, the process manager, the communication manager, and adapters for various domains. The RPD model interpreter matches the current situation with known experinces, which are organized into a hierarchy. Missing cues relevant to the current decision are identified. The information manager uses the information dependency in the knowledge base to infer missing information that is relevant to the higher-level cues, option evaluations, and anomalies. The communication manager then contact agents that provide the missing information. To build a model, one has to (a) determine what components are involved to compose the model, (b) analyze tasks and elicit relevant knowledge for the components, and (c) develop domain adapter to integrate agents to the external environment.
R-CAST agents have been used to develop decision-making aids for human teams. They have also be used to study team cognition and issues related to human-agent collaboration in time-stressed application domains.
Group decision support systems
Group Decision Support Systems are a class of electronic meeting systems, a collaboration technology designed to support meetings and group work...
based on research on naturalistic decision making
Naturalistic decision making
The naturalistic decision making framework emerged as a means of studying how people actually make decisions and perform cognitively complex functions in demanding situations...
. Its architecture, based on multiple software agents, supports decision-making teams by anticipating information relevant to their decisions based on a shared mental model about the context of decision making.
Principles of design
In this digital information age, decision-making teams are often flooded with an overwhelming amount of information. This leads to two challenges:- First, a human decision maker can be overloaded with information and have difficulty making good decisions in a timely manner.
- Second, members of a team may have difficulty determining what information a teammate actually needs, and hence what information needs to be shared with him/her.
The R-CAST technology aims to address both of these challenges.
The R-CAST approach is based on four major concepts:
- Agents use a model of human decision making process (called recognition primed decisionRecognition primed decisionRecognition-primed decision is a model of how people make quick, effective decisions when faced with complex situations. In this model, the decision maker is assumed to generate a possible course of action, compare it to the constraints imposed by the situation, and select the first course of...
[RPD] model) to link decision-making tasks to information relevant to the decisions. - The computational RPD model in R-CAST uses a knowledge structure (called experience knowledge) that captures knowledge relevant to decision-making.
- Three types of relevant information can be anticipated from experience knowledge and inference rules, relating to:
- matching current situation to known experience (i.e., cues),
- evaluating multiple decision options, and
- detecting anomalies after a decision is made so that the original decision can be modified accordingly.
- The computational RPD model serves as a shared DM process between agents and human in a team, which enables agents to share relevant information to other teammates, whether they are software agents or human.
Principles of operation
In addition to anticipating information needed for decision makings, R-CAST agents also collaborate to seek and fuse information in a distributed environment such as Service-oriented architecture. R-CAST is developed at the Intelligent Agents Laboratory in the College of Information Sciences and Technology at Pennsylvania State UniversityPennsylvania State University
The Pennsylvania State University, commonly referred to as Penn State or PSU, is a public research university with campuses and facilities throughout the state of Pennsylvania, United States. Founded in 1855, the university has a threefold mission of teaching, research, and public service...
, led by Dr. John Yen
John Yen
John Yen is University Professor and Associate Dean for Research and Graduate Programs in the at Pennsylvania State University. He is also the Director of the there....
.
The R-CAST architecture is component-based and reconfigurable. By selecting components suitable for an application, R-CAST can be configured into a wide range of agents: from simple reflex agents to RPD-enabled agents. Key components of R-CAST include the RPD model interpreter, the knowledge base, the information manager, the process manager, the communication manager, and adapters for various domains. The RPD model interpreter matches the current situation with known experinces, which are organized into a hierarchy. Missing cues relevant to the current decision are identified. The information manager uses the information dependency in the knowledge base to infer missing information that is relevant to the higher-level cues, option evaluations, and anomalies. The communication manager then contact agents that provide the missing information. To build a model, one has to (a) determine what components are involved to compose the model, (b) analyze tasks and elicit relevant knowledge for the components, and (c) develop domain adapter to integrate agents to the external environment.
R-CAST agents have been used to develop decision-making aids for human teams. They have also be used to study team cognition and issues related to human-agent collaboration in time-stressed application domains.
Publications
- Xiaocong Fan, Bingjun Sun, Shuang Sun, Michael McNeese, and John Yen, RPD-Enabled Agents Teaming with Humans for Multi-Context Decision Making, AAMAS 2006
- X. Fan, S. Sun, M. McNeese, and J. Yen, Extending Recognition-Primed Decision Model For Human-Agent Collaboration, In Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multi Agent Systems, pp. 945–952, The Netherlands, July 25–29, 2005.
- X. Fan, S. Sun, B. Sun, G. Airy, M. McNeese, J. Yen, Collaborative RPD-Enabled Agents Assisting the Three-Block Challenge in Command and Control in Complex and Urban Terrain, In Proceedings of 2005 Conference on Behavior Representation in Modeling and Simulation (BRIMS), pp. 113–123, Universal City, CA, May 16–19, 2005.
- X. Fan, S. Sun, and J. Yen, On Shared Situation Awareness for Supporting Human Decision-Making Teams, In Proceedings of 2005 AAAI Spring Symposium on AI Technologies for Homeland Security, pp. 17–24, Stanford, CA, Mar. 2005.
See also
- Intelligent agentIntelligent agentIn 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...
- Cognitive architectureCognitive architectureA 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 - IA considered to be self-aware - Multi-agent systemMulti-agent systemA 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...
- Agent-based model
External links
- Intelligent Agent Laboratory, the Pennsylvania State UniversityPennsylvania State UniversityThe Pennsylvania State University, commonly referred to as Penn State or PSU, is a public research university with campuses and facilities throughout the state of Pennsylvania, United States. Founded in 1855, the university has a threefold mission of teaching, research, and public service...
- Dr. John Yen