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CEC
2005
IEEE

Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma

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Population based incremental learning with guided mutation versus genetic algorithms: iterated prisoners dilemma
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.
Timothy Gosling, Nanlin Jin, Edward P. K. Tsang
Added 13 Oct 2010
Updated 13 Oct 2010
Type Conference
Year 2005
Where CEC
Authors Timothy Gosling, Nanlin Jin, Edward P. K. Tsang
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