Scientific Research and Essays | |
Adaptive automata model for learning opponent behavior based on genetic algorithms | |
Sally Almanasra1  | |
关键词: Game Theory; Prisoner’ s Dilemma; genetic algorithms; adaptive automata.; | |
DOI : 10.5897/SRE11.1860 | |
学科分类:社会科学、人文和艺术(综合) | |
来源: Academic Journals | |
【 摘 要 】
The purpose of this research is to study how genetic algorithms (GA's) are applied in the field of Game Theory. GA's are effective approaches for machine learning and optimization problems. In this work, genetic algorithm is utilized to determine the behavior of an opponent in Prisoners’ Dilemma. The opponent behavior will be modeled by means of adaptive automaton. The basic problem of this study is the well-known Prisoner Dilemma. The primary purpose of this research is to determine the opponent behavior towards finding a better strategy to be followed by the player, since the best strategy to be followed depends on the opponent behavior. The results of our proposed model showed the capability of our model to identify the opponent model efficiently. Based on the provided knowledge about the opponent model, the dynamic strategy showed better results when compared to other well-known strategies.
【 授权许可】
CC BY
【 预 览 】
Files | Size | Format | View |
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RO201902011596103ZK.pdf | 651KB | download |