Population Based Incremental Learning with Guided Mutation Versus Genetic Algorithms: Iterated Prisoners Dilemma

Gosling, Timothy, Jin, Nanlin and Tsang, Edward (2005) Population Based Incremental Learning with Guided Mutation Versus Genetic Algorithms: Iterated Prisoners Dilemma. In: Congress on Evolutionary Computation, 2 - 5 September 2005, Edinburgh, Scotland.

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Abstract

Axelrod's original experiments for evolving IPD player strategies involved the use of a basic GA. In this paper we examine how well a simple GA performs against the more recent Population Based Incremental Learning system under similar conditions. We find that GA performs slightly better than standard PBIL under most conditions. This differnce in performance can be mitigated and reversed through the use of a 'guided' mutation operator.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	H400 Aerospace Engineering
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Becky Skoyles
Date Deposited:	11 Aug 2014 11:46
Last Modified:	13 Oct 2019 00:24
URI:	http://nrl.northumbria.ac.uk/id/eprint/17382

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