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Swafford, John Mark
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Swafford, John Mark
Official Name
Swafford, John Mark
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Now showing 1 - 2 of 2
- PublicationComparing the performance of the evolvable πgrammatical evolution genotype-phenotype pap to grammatical evolution in the dynamic Ms. Pac-Man environment(IEEE, 2010-07)
; ; ; ; ; ; In this work, we examine the capabilities of two forms of mappings by means of Grammatical Evolution (GE) to successfully generate controllers by combining high-level functions in a dynamic environment. In this work we adopted the Ms. Pac-Man game as a benchmark test bed. We show that the standard GE mapping and Position Independent GE (πGE) mapping achieve similar performance in terms of maximising the score. We also show that the controllers produced by both approaches have an overall better performance in terms of maximising the score compared to a hand-coded agent. There are, however, significant differences in the controllers produced by these two approaches: standard GE produces more controllers with invalid code, whereas the opposite is seen with πGE.564Scopus© Citations 11 - PublicationEvolving a Ms. PacMan controller using grammatical evolutionIn this paper we propose an evolutionary approach capable of successfully combining rules to play the popular video game, Ms. Pac- Man. In particular we focus our attention on the benefits of using Gram- matical Evolution to combine rules in the form of “if then perform ”. We defined a set of high-level functions that we think are necessary to successufully maneuver Ms. Pac-Man through a maze while trying to get the highest possible score. For comparison purposes, we used four Ms. Pac-Man agents, including a hand-coded agent, and tested them against three different ghosts teams. Our approach shows that the evolved controller achieved the highest score among all the other tested controllers, regardless of the ghost team used.
Scopus© Citations 22 807