An Analysis of Genotype-Phenotype Maps in Grammatical Evolution

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.

[1]  Riccardo Poli,et al.  A Field Guide to Genetic Programming , 2008 .

[2]  Anthony Brabazon,et al.  An Analysis of the Behaviour of Mutation in Grammatical Evolution , 2010, EuroGP.

[3]  John R. Koza,et al.  Genetic Programming IV: Routine Human-Competitive Machine Intelligence , 2003 .

[4]  W. Langdon.  An Analysis of the MAX Problem in Genetic Programming , 1997 .

[5]  Michael O'Neill,et al.  Grammatical evolution - evolutionary automatic programming in an arbitrary language , 2003, Genetic programming.

[6]  Victor Ciesielski,et al.  Linear genetic programming , 2008, Genetic Programming and Evolvable Machines.

[7]  Reinhard Männer,et al.  Parallel Problem Solving from Nature — PPSN III , 1994, Lecture Notes in Computer Science.

[8]  Erik Hemberg,et al.  Pre-, In-and Postfix grammars for Symbolic Regression in Grammatical Evolution , 2008 .

[9]  S. B. Atienza-Samols,et al.  With Contributions by , 1978 .

[10]  Julian Francis Miller,et al.  Evolution, development and learning using self-modifying cartesian genetic programming , 2009, GECCO '09.

[11]  Julian Francis Miller,et al.  Cartesian genetic programming , 2000, GECCO '10.

[12]  Riccardo Poli,et al.  Genetic and Evolutionary Computation – GECCO 2004 , 2004, Lecture Notes in Computer Science.

[13]  Anthony Brabazon,et al.  GEVA: grammatical evolution in Java , 2008, SEVO.

[14]  C. Stephens.  Effect of mutation and recombination on the genotype-phenotype map , 1999, nlin/0006051.

[15]  Anthony Brabazon,et al.  Foundations in Grammatical Evolution for Dynamic Environments , 2009, Studies in Computational Intelligence.

[16]  Riccardo Poli,et al.  Genetic Programming: An Introduction and Tutorial, with a Survey of Techniques and Applications , 2008, Computational Intelligence: A Compendium.

[17]  Wolfgang Banzhaf,et al.  Genotype-Phenotype-Mapping and Neutral Variation - A Case Study in Genetic Programming , 1994, PPSN.

[18]  Antonia J. Jones,et al.  An Adaptive Mapping for Developmental Genetic Programming , 2001, EuroGP.

[19]  Wolfgang Banzhaf,et al.  Evolution of genetic code on a hard problem , 2001 .

[20]  José Luis Fernández-Villacañas Martín,et al.  Investigation of the importance of the genotype-phenotype mapping in information retrieval , 2003, Future Gener. Comput. Syst..

[21]  Douglas B Kell,et al.  Genotype-phenotype mapping: genes as computer programs. , 2002, Trends in genetics : TIG.

[22]  Conor Ryan,et al.  Grammatical Evolution , 2001, Genetic Programming Series.

[23]  Anthony Brabazon,et al.  pi-Grammatical Evolution , 2004, GECCO.

[24]  W. Banzhaf,et al.  Genetic programming using genotype-phenotype mapping from linear genomes into linear phenotypes , 1996 .