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

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)
sequential bargaining game,  artificial agent,  statistics analysis,  genetic algorithm,  reinforcement learning,  

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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.