An evolutionary model of multi-agent learning with a varying exploration rate

Authors:
M. Kaisers;K. Tuyls;S. Parsons;F. Thuijsman
Affiliations:
Eindhoven University of Tech, Eindhoven, The Netherlands;Eindhoven University of Tech, Eindhoven, The Netherlands;Brooklyn College, Brooklyn, New York;Maastricht University, Maastricht, The Netherlands
Venue:
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Year:
2009

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Abstract

Multi-agent learning is a challenging problem and has recently attracted increased attention by the research community [4, 5]. It promises control over complex multi-agent systems such that agents enact a global desired behavior while operating on local knowledge.