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http://dx.doi.org/10.5392/JKCA.2020.20.12.278

Analysis on Iterated Prisoner's Dilemma Game using Binary Particle Swarm Optimization  

Lee, Sangwook (목원대학교 정보통신융합공학부)
Publication Information
The Journal of the Korea Contents Association / v.20, no.12, 2020 , pp. 278-286 More about this Journal
Abstract
The prisoner's dilemma game which is a representative example of game theory is being studied with interest by many economists, social scientists, and computer scientists. In recent years, many researches on computational approaches that apply evolutionary computation techniques such as genetic algorithms and particle swarm optimization have been actively conducted to analyze prisoner dilemma games. In this study, we intend to evolve a strategy for a iterated prisoner dilemma game participating two or more players using three different binary particle swarm optimization techniques. As a result of experimenting by applying three kinds of binary particle swarm optimization to the iterated prisoner's dilemma game, it was confirmed that mutual cooperation can be established even among selfish participants to maximize their own gains. However, it was also confirmed that the more participants, the more difficult to establish a mutual cooperation relationship.
Keywords
Iterated Prisoner's Dilemma Game; Binary Particle Swarm Optimization; Evolution; Cooperation; Defection;
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Times Cited By KSCI : 1  (Citation Analysis)
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