Physical Sciences and Mathematics Commons^™

Learning Situation-Specific Coordination In Cooperative Multi-Agent Systems, M. V. Nagendra Prasad, Victor R. Lesser

Computer Science Department Faculty Publication Series

Achieving effective cooperation in a multi-agent system is a difficult problem for a number of reasons such as limited and possiblyout-dated views of activitiesof other agents and uncertainty about the outcomes of interacting non-local tasks. In this paper, we present a learning system called COLLAGE, that endows the agents with the capability to learn how to choose the most appropriate coordination strategy from a set of available coordination strategies. COLLAGE relies onmeta-level information about agents’ problemsolving situations to guide themtowards a suitable choice for a coordination strategy. We present empirical results that strongly indicate the effectiveness of the learning algorithm.