Cooperation, solution concepts and long-term dynamics in the iterated prisoner's dilemma

Julian Garcia, German Hernandez, Juan Carlos Galeano

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Abstract

Solution concepts help designing co-evolutionary algorithms by interfacing search mechanisms and problems. This work analyses co-evolutionary dynamics by coupling the notion of solution concept with a Markov chain model of coevolution. It is shown that once stationarity has been reached by the Markov chain, and given a particular solution concept of interest, the dynamics can be seen as a Bernoulli process describing how the algorithm visits solution and non-solution sets. A particular analysis is presented using the Iterated Prisoner's Dilemma. By numerically computing the Markov chain transition matrices and stationary distributions, a complex and strong relation between variation and selection is observed.

Original languageEnglish
Title of host publication2006 IEEE Congress on Evolutionary Computation, CEC 2006
Pages1618-1623
Number of pages6
Publication statusPublished - 1 Dec 2006
Externally publishedYes
EventIEEE Congress on Evolutionary Computation 2006 - Vancouver, Canada
Duration: 16 Jul 200621 Jul 2006
https://ieeexplore.ieee.org/xpl/conhome/11108/proceeding (Proceedings)

Conference

ConferenceIEEE Congress on Evolutionary Computation 2006
Abbreviated titleIEEE CEC 2006
CountryCanada
CityVancouver
Period16/07/0621/07/06
Internet address

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