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

Julian Garcia, German Hernandez, Juan Carlos Galeano

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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
Event2006 IEEE Congress on Evolutionary Computation, CEC 2006 - Vancouver, BC, Canada
Duration: 16 Jul 200621 Jul 2006

Conference

Conference2006 IEEE Congress on Evolutionary Computation, CEC 2006
CountryCanada
CityVancouver, BC
Period16/07/0621/07/06

Cite this

Garcia, J., Hernandez, G., & Galeano, J. C. (2006). Cooperation, solution concepts and long-term dynamics in the iterated prisoner's dilemma. In 2006 IEEE Congress on Evolutionary Computation, CEC 2006 (pp. 1618-1623). [1688502]