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Comparing the Performance of the Evolvable piGrammatical Evolution Genotype-Phenotype Map to Grammatical Evolution in the Dynamic Ms. Pac-Man Environment
BibTeX
@MISC{Fagan_comparingthe,
author = {David Fagan and Eoin Murphy and John Mark Swafford and Ros Agapitos and Anthony Brabazon},
title = {Comparing the Performance of the Evolvable piGrammatical Evolution Genotype-Phenotype Map to Grammatical Evolution in the Dynamic Ms. Pac-Man Environment},
year = {}
}
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Abstract
Abstract — 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 (piGE) 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 piGE. I.
