FUZZY REINFORCEMENT LEARNING FOR EMBEDDED SOCCER AGENTS IN A MULTI-AGENT CONTEXT

Abstract
The work presented in this paper aims at combining fuzzy functionapproximation and reinforcement learning in order to create roboticsoccer agents that are able to coordinate their behaviours locallyand socially while learning from experience.

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