### 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 language | English |
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Title of host publication | 2006 IEEE Congress on Evolutionary Computation, CEC 2006 |

Pages | 1618-1623 |

Number of pages | 6 |

Publication status | Published - 1 Dec 2006 |

Externally published | Yes |

Event | 2006 IEEE Congress on Evolutionary Computation, CEC 2006 - Vancouver, BC, Canada Duration: 16 Jul 2006 → 21 Jul 2006 |

### Conference

Conference | 2006 IEEE Congress on Evolutionary Computation, CEC 2006 |
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Country | Canada |

City | Vancouver, BC |

Period | 16/07/06 → 21/07/06 |

## Cite this

*2006 IEEE Congress on Evolutionary Computation, CEC 2006*(pp. 1618-1623). [1688502]