intelligent agent
Distributed Intelligent Agents
Katia Sycara
Keith Decker
Anandeep Pannu
Mike Williamson
Dajun Zeng
The Robotics Institute
Carnegie Mellon University
Pittsburgh, PA 15213, U.S.A.
Voice: (412) 268-8825 Fax: (412) 268-5569
URL: http://www.cs.cmu.edu/ softagents/
Abstract
We are investigating techniques for developing distributed and adaptive collections of agents that coordinate to retrieve, lter and fuse information relevant to the user, task and situation, as well as anticipate a user 's information needs. In our system of agents, information gathering is seamlessly integrated with decision support.
The task for which particular information is requested of the agents does not remain in the user 's head but it is explicitly represented and supported through agent collaboration. In this paper we present the distributed system architecture, agent collaboration interactions, and a reusable set of software components for constructing agents. We call this reusable multi-agent computational infrastructure RETSINA
(Reusable Task Structure-based Intelligent Network Agents). It has three types of agents. Interface agents interact with the user receiving user speci cations and delivering results. They acquire, model, and utilize user preferences to guide system coordination in support of the user 's tasks. Task agents help users perform tasks by formulating problem solving plans and carrying out these plans through querying and exchanging information with other software agents. Information agents provide intelligent access to a heterogeneous collection of information sources. We have implemented this system framework and are
developing collaborating agents in diverse complex real world tasks, such as organizational decision making (the PLEIADES system), and nancial portfolio management (the WARREN system).
1 Introduction
E ective use of the Internet by humans or decision support machine systems has been hampered by some dominant
Katia Sycara
Keith Decker
Anandeep Pannu
Mike Williamson
Dajun Zeng
The Robotics Institute
Carnegie Mellon University
Pittsburgh, PA 15213, U.S.A.
Voice: (412) 268-8825 Fax: (412) 268-5569
URL: http://www.cs.cmu.edu/ softagents/
Abstract
We are investigating techniques for developing distributed and adaptive collections of agents that coordinate to retrieve, lter and fuse information relevant to the user, task and situation, as well as anticipate a user 's information needs. In our system of agents, information gathering is seamlessly integrated with decision support.
The task for which particular information is requested of the agents does not remain in the user 's head but it is explicitly represented and supported through agent collaboration. In this paper we present the distributed system architecture, agent collaboration interactions, and a reusable set of software components for constructing agents. We call this reusable multi-agent computational infrastructure RETSINA
(Reusable Task Structure-based Intelligent Network Agents). It has three types of agents. Interface agents interact with the user receiving user speci cations and delivering results. They acquire, model, and utilize user preferences to guide system coordination in support of the user 's tasks. Task agents help users perform tasks by formulating problem solving plans and carrying out these plans through querying and exchanging information with other software agents. Information agents provide intelligent access to a heterogeneous collection of information sources. We have implemented this system framework and are
developing collaborating agents in diverse complex real world tasks, such as organizational decision making (the PLEIADES system), and nancial portfolio management (the WARREN system).
1 Introduction
E ective use of the Internet by humans or decision support machine systems has been hampered by some dominant
References: 1] P. R. Cohen and H. J. Levesque. Intention=choice + commitment. In Proceedings of AAAI-87, pages 410{415, Seattle, WA., 1987 4] Keith Decker. Environment Centered Analysis and Design of Coordination Mechanisms. PhD thesis, University of Massachusetts, 1995. National Conference on Arti cial Intelligence. AAAI, 1992. of the ACM, 37(7):48{53,147, 1994. 13] Kan Lang. Newsweeder: Learning to lter netnews. In Proceedings of Machine Learning Conference, 1995. In 1996 AAAI Symposium on Machine Learning and Information Access, 1996. 20] Y. Shoham. Agent-oriented programming. Arti cial Intelligence, 60(1):51{92, 1993. 21] Reid Simmons. Structured control for autonomous robots. IEEE Journal of Robotics and Automation, 1994. 23] Katia Sycara and Dajun Zeng. Coordination of multiple intelligent software agents. International Journal of Cooperative Information Systems, To Appear, 1996. Multiagent Systems, 1996.