An Analysis of Genotype-Phenotype Maps in Grammatical Evolution

Abstract

Abstract. We present an analysis of the genotype-phenotype map in Grammatical Evolution (GE). The standard map adopted in GE is a depth-first expansion of the non-terminal symbols during the derivation sequence. Earlier studies have indicated that allowing the path of the expansion to be under the guidance of evolution as opposed to a deterministic process produced significant performance gains on all of the benchmark problems analysed. In this study we extend this analysis to include a breadth-first and random map, investigate additional benchmark problems, and take into consideration the implications of recent results on alternative grammar representations with this new evidence. We conclude that it is possible to improve the performance of grammar-based Genetic Programming by the manner in which a genotype-phenotype map is performed.

Comparing the performance of the evolvable πGrammatical Evolution genotype-phenotype map to Grammatical Evolution in the dynamic Ms. Pac-Man environment

“…Position Independent GE (πGE) [9], [2] is almost identical in operation to standard GE except when it comes to the mapping process. As shown above, GE always takes the left-most non-terminal to be expanded next during the mapping from genotype to phenotype.…”

“…πGE has been reported to have a better overall performance in terms of finding better results compared to standard GE as shown in [9], [2]. The objective of this paper is to see the utility of both forms of mappings on a dynamic problem.…”

Investigation of the Performance of Different Mapping Orders for GE on the Max Problem

“…Previous work [4] showed a significant reduction in the performance of GE on the Max problem once the πGE genotype-phenotype map was applied. This was a very surprising result as previous studies by O'Neill et al [18] had not shown a similar type of performance reduction in any of the benchmark problems in that study.…”

Genotype-phenotype mapping in dynamic environments with grammatical evolution

“…Can further inspiration be taken from biology which first inspired the GPM in GP to improve the EA. Recently these topics have started to be tackled [8,15,6,7,1,14], but many more avenues of exploration remain as the interpretation of mapping used by GE is simplistic and lacking in some of the desired advanced features of the GPM that exist in nature [3].…”