DocumentCode :
1795833
Title :
The impact of agent size and number of rounds on cooperation in the iterated Prisoner´s Dilemma
Author :
Barlow, Lee-Ann
Author_Institution :
Dept. of Math. & Stat., Univ. of Guelph, Guelph, ON, Canada
fYear :
2014
fDate :
9-12 Dec. 2014
Firstpage :
120
Lastpage :
127
Abstract :
The chance that a population of iterated Prisoner´s Dilemma playing agents will evolve to a cooperative state is strongly influenced by the duration of the encounter. With only one round of Prisoner´s Dilemma, the populations rapidly evolve to the always-defect Nash equilibrium. Durations exceeding the number of rounds to which the agent representation could conceivably count are most likely to yield cooperation but require more computer resources. Reported here is a careful study of different encounter lengths and their impact on cooperation using finite state machines, which are known to yield high levels of cooperation for long encounter durations. Agents with different numbers of states are used. This research, in addition to highlighting one of the boundaries of the evolution of cooperation for evolving agents, serves as a parameter setting study for future research that permits a reduction in the computational resources required. A recently developed tool known as a play profile is used to determine the distribution of agent behaviour by sorting the final fitness scores achieved in each important epoch of evolution. It was found that only 41 to 64 rounds are required to achieve the same level of cooperation as that achieved in 150 rounds, with conservative estimates lying between 60 and 85 rounds. Even the conservative estimates include approximately half as many rounds of play as the current standard.
Keywords :
finite state machines; game theory; multi-agent systems; Nash equilibrium; agent behaviour; agent cooperation; agent representation; agent size; finite state machines; iterated Prisoners dilemma game; Biological system modeling; Entropy; Evolutionary computation; Games; Sociology; Standards; Statistics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Foundations of Computational Intelligence (FOCI), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/FOCI.2014.7007816
Filename :
7007816
Link To Document :
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