DocumentCode :
2227435
Title :
Strange evolution behavior of 7-bit binary string strategies in iterated prisoner´s dilemma game
Author :
Sudo, Takahiko ; Goto, Kazushi ; Nojima, Yusuke ; Ishibuchi, Hisao
Author_Institution :
Department of Computer Science and Intelligent Systems, Graduate School of Engineering, Osaka Prefecture University, Sakai, Osaka 599-8531, Japan
fYear :
2015
fDate :
25-28 May 2015
Firstpage :
3346
Lastpage :
3353
Abstract :
The prisoner´s dilemma (PD) game is a well-known non-zero sum game. Its iterated version (IPD game) has been widely used to study the evolution of cooperative strategies. In this paper, we assume a noisy environment where a player chooses a different action from the suggested one by its own strategy with a pre-specified error probability. Generally, the noise in action selection makes the evolution of cooperation difficult because the player cannot distinguish between an intentional defection by the opponent´s strategy and an unintentional defection by error. However, when a 7-bit binary string with a memory about opponent´s two actions was used as a strategy of each player, we observed strange evolution behavior where the use of a small error probability increased the average payoff to the level close to the complete mutual cooperation. That is, the use of a small error probability seems to help the evolution of cooperation. Such a strange behavior was not clearly observed by other types of strategies (e.g., 3-bit binary string with a memory about opponent´s single action, 15-bit binary strings with a memory about opponent´s three actions). In this paper, we report our simulation results where our focus is placed on the strange evolution behavior of 7-bit binary string strategies. We also try to analyze their strange evolution behavior.
Keywords :
Computer simulation; Error probability; Games; Noise measurement; Sociology; Statistics; error probability; evolution of cooperation; evolutionary games; game strategies; iterated prisoner´s dilemma (IPD);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location :
Sendai, Japan
Type :
conf
DOI :
10.1109/CEC.2015.7257309
Filename :
7257309
Link To Document :
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