The Bases of Effective Coordination in Decentralized Multi-Agent Systems

Coordination is a recurring theme in multiagent systems design. We consider the problem of achieving coordination in a system where the agents make autonomous decisions based solely on local knowledge. An open theoretical issue is what goes into achieving effective coordination? There is some folklore about the importance of the knowledge held by the different agents, but the rest of the rich agent landscape has not been explored in depth. The present paper seeks to delineate the different components of an abstract architecture for agents that influence the effectiveness of coordination. Specifically, it proposes that the extent of the choices available to the agents as well as the extent of the knowledge shared by them are both important for understanding coordination in general. These lead to a richer view of coordination that supports a more intuitive set of claims. This paper supports its conceptual conclusions with experimental results based on simulation.

[1]  Anand S. Rao,et al.  An architecture for real-time reasoning and system control , 1992, IEEE Expert.

[2]  Paul R. Cohen,et al.  Empirical methods for artificial intelligence , 1995, IEEE Expert.

[3]  R. Kirk CONVENTION: A PHILOSOPHICAL STUDY , 1970 .

[4]  S. Clearwater Market-based control: a paradigm for distributed resource allocation , 1996 .

[5]  W. Hamilton,et al.  The evolution of cooperation. , 1984, Science.

[6]  Moshe Tennenholtz,et al.  Adaptive Load Balancing: A Study in Multi-Agent Learning , 1994, J. Artif. Intell. Res..

[7]  John Rachlin,et al.  A-Teams: An Agent Architecture for Optimization and Decision Support , 1998, ATAL.

[8]  W. Hamilton,et al.  The Evolution of Cooperation , 1984 .

[9]  Herbert A. Simon,et al.  The Sciences of the Artificial , 1970 .

[10]  T. Ishida,et al.  An equilibratory market-based approach for distributed resource allocation and its applications to communication network control , 1996 .

[11]  Tad Hogg,et al.  Controlling chaos in distributed systems , 1991, IEEE Trans. Syst. Man Cybern..

[12]  Munindar P. Singh Commitments in the Architecture of a Limited, Rational Agent , 1996, PRICAI Workshop on Intelligent Agent Systems.

[13]  Munindar P. Singh,et al.  Formal methods in DAI: logic-based representation and reasoning , 1999 .

[14]  Gerhard Weiss,et al.  Multiagent systems: a modern approach to distributed artificial intelligence , 1999 .

[15]  Edmund H. Durfee,et al.  Coordination of distributed problem solvers , 1988 .

[16]  Somesh Jha,et al.  Increasing Resource Utilization and Task Performance by Agent Cloning , 1998, ATAL.

[17]  Eithan Ephrati,et al.  Experimental Investigation Of An Agent Commitment Strategy , 1994 .

[18]  David Lewis Convention: A Philosophical Study , 1986 .

[19]  David Kinny The Agentis Agent Interaction Model , 1998, ATAL.

[20]  Sandip Sen,et al.  Effects of Local Information on Group Behavior , 1996, AAAI/IAAI, Vol. 2.

[21]  Michael P. Georgeff,et al.  Commitment and Effectiveness of Situated Agents , 1991, IJCAI.