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Evolutionary game theory and multi-agent reinforcement learning

Published online by Cambridge University Press:  01 December 2005

KARL TUYLS  and
ANN NOWÉ
KARL TUYLS
Affiliation:
University of Maastricht, Institute for Knowledge and Agent Technology (IKAT), The Netherlands; E-mail: k.tuyls@cs.unimaas.nl
ANN NOWÉ
Affiliation:
Computational Modeling Lab, Vrije Universiteit Brussel, Brussels, Belgium; E-mail: asnowe@info.vub.ac.be
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Abstract

In this paper we survey the basics of reinforcement learning and (evolutionary) game theory, applied to the field of multi-agent systems. This paper contains three parts. We start with an overview on the fundamentals of reinforcement learning. Next we summarize the most important aspects of evolutionary game theory. Finally, we discuss the state-of-the-art of multi-agent reinforcement learning and the mathematical connection with evolutionary game theory.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 20 , Issue 1 , March 2005 , pp. 63 - 90
Copyright
© 2006 Cambridge University Press

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