Learning Situation-Specific Coordination in Cooperative Multi-agent Systems

Achieving effective cooperation in a multi-agent system is a difficult problem for a number of reasons such as limited and possiblyout-datedviews 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 on meta-level information about agents' problem solvingsituationsto guide them towards a suitable choice for a coordination strategy. We present empirical results that strongly indicate the effectiveness of the learning algorithm.

• Type: Journal
• Year: 1999
• Where: AAMAS
• Authors: M. V. Nagendra Prasad, Victor R. Lesser
• Keywords: AAMAS 1999, Appropriate Coordination Strategy, Available Coordination Strategies, Coordination Strategy, Intelligent Agents