NDLI: Fingerprint analysis of the noisy prisoner’s dilemma

Content Provider	IEEE Xplore Digital Library
Author	Ashlock, D. Eun-Youn Kim Ashlock, W.
Copyright Year	2007
Description	Author affiliation: Univ. of Guelph, Guelph (Ashlock, D.)
Abstract	Fingerprinting is a technique that permits the identification of strategies for playing a game without doing detailed hand analysis. In this study the evolution of strategies for playing the iterated prisoner's dilemma in the presence of noise was analyzed using fingerprinting and other techniques. Agents were evolved for 6400 generations taking samples at eight exponentially-spaced epochs with noise levels of 0, 1, and 5 percent. Populations were tested for probability of cooperative play, for competitive ability against agents evolved with different noise levels, for competitive ability against agents from other epochs, and for their distribution of strategy types. The ability of agents in noisy environments to cooperate was significantly enhanced over evolutionary time with substantial gains in cooperation made after the 3000 generation. Also, evolution in the presence of noise was found to significantly improve an agent's competitive ability. Agents evolved for a longer time tended to beat agents evolved for a shorter time, though there were some intriguing exceptions. And, populations evolved in the presence of noise had significantly different strategy distributions than populations evolved without noise.
Starting Page	4073
Ending Page	4080
File Size	120929
Page Count	8
File Format	PDF
ISBN	9781424413393
DOI	10.1109/CEC.2007.4425002
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-25
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fingerprint recognition Mathematics Statistical analysis Noise level Working environment noise Biological system modeling Automata Testing Noise generators Game theory
Content Type	Text
Resource Type	Article

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