An Evolutionary Game Theoretic Perspective on Learning in Multi-Agent Systems |
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Authors: | Tuyls Karl Nowe Ann Lenaerts Tom Manderick Bernard |
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Affiliation: | (1) Computational Modeling Lab Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium |
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Abstract: | In this paper we revise Reinforcement Learning and adaptiveness in Multi-Agent Systems from an Evolutionary Game Theoretic perspective. More precisely we show there is a triangular relation between the fields of Multi-Agent Systems, Reinforcement Learning and Evolutionary Game Theory. We illustrate how these new insights can contribute to a better understanding of learning in MAS and to new improved learning algorithms. All three fields are introduced in a self-contained manner. Each relation is discussed in detail with the necessary background information to understand it, along with major references to relevant work. |
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