Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/734
Title: An Evolutionary Game Theoretic Perspective on Learning in Multi-Agent Systems
Authors: TUYLS, Karl 
Lenaerts, Tom
Manderick, Bernard
Issue Date: 2004
Publisher: Springer
Source: Synthese, 139(2). p. 297-330
Abstract: In this paper we revise Reinforcement Learning andadaptiveness in Multi-Agent Systems from an EvolutionaryGame Theoretic perspective. More precisely we show thereis a triangular relation between the fields of Multi-AgentSystems, Reinforcement Learning and Evolutionary Game Theory.We illustrate how these new insights can contribute to a betterunderstanding of learning in MAS and to new improved learningalgorithms. All three fields are introduced in a self- containedmanner. Each relation is discussed in detail with thenecessary background information to understand it, alongwith major references to relevant work
Document URI: http://hdl.handle.net/1942/734
ISSN: 0039-7857
e-ISSN: 1573-0964
DOI: 10.1023/B:SYNT.0000024908.89191.f1
ISI #: 000220957200006
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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