DocumentCode
2715750
Title
Cooperation in Prisoner´s Dilemma on Graphs
Author
Ashlock, Daniel A.
Author_Institution
Math. & Stat., Guelph Univ., Ont.
fYear
2007
fDate
1-5 April 2007
Firstpage
48
Lastpage
55
Abstract
A combinatorial graph can be used to place a geography on a population of evolving agents. In this paper agents are trained to play prisoner´s dilemma while situated on combinatorial graphs. A collection of thirteen different combinatorial graphs is used. The graph always limits which agents can mate during reproduction. Two sets of experiments are performed for each graph: one in which agents only play prisoners dilemma against their neighbors and one in which fitness is evaluated by a round robin tournament among all population members. Populations are evaluated on their level of cooperativeness, the type of play they engage in, and by identifying the type and diversity of strategies that are present. This latter analysis relies on the fingerprinting of players, a representation-independent method of identifying strategies. Changing the combinatorial graph on which a population lives is found to yield statistically significant changes in the character of the evolved populations for all the metrics used
Keywords
evolutionary computation; game theory; graph theory; software agents; statistical analysis; combinatorial graph; evolutionary computation; evolving agents; geography; prisoner dilemma; round robin tournament; spatial algorithm; Automata; Biological system modeling; Computational intelligence; Evolution (biology); Evolutionary computation; Fingerprint recognition; Geography; Mathematics; Neural networks; Statistics; Evolutionary Computation; Prisoner´s Dilemma; Spatial Algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Games, 2007. CIG 2007. IEEE Symposium on
Conference_Location
Honolulu, HI
Print_ISBN
1-4244-0709-5
Type
conf
DOI
10.1109/CIG.2007.368078
Filename
4219023
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