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Analysis on the Parameters of the Evolving Artificial Agents in Sequential Bargaining Game
Seok-Cheol CHANG Joung-Il YUN Ju-Sang LEE Sang-Uk LEE Nitaigour-Premchand MAHALIK Byung-Ha AHN
Publication
IEICE TRANSACTIONS on Information and Systems
Vol.E88-D
No.9
pp.2098-2101 Publication Date: 2005/09/01 Online ISSN:
DOI: 10.1093/ietisy/e88-d.9.2098 Print ISSN: 0916-8532 Type of Manuscript: Special Section LETTER (Special Section on Software Agent and Its Applications) Category: Keyword: sequential bargaining game, artificial agent, statistics analysis, genetic algorithm, reinforcement learning,
Full Text: PDF(339.7KB)>>
Summary:
Over the past few years, a considerable number of studies have been conducted on modeling the bargaining game using artificial agents on within-model interaction. However, very few attempts have been made at study on the interaction and co-evolutionary process among heterogeneous artificial agents. Therefore, we present two kinds of artificial agents, based on genetic algorithm (GA) and reinforcement learning (RL), which play a game on between-model interaction. We investigate their co-evolutionary processes and analyze their parameters using the analysis of variance.
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