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 difference in performance can be mitigated and reversed through the use of a `guided´ mutation operator