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Analysis on the Parameters of the Evolving Artificial Agents in Sequential Bargaining Game
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2005/09/01
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.