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 de-terministic process produced significant performance gains on all of the benchmark problems analysed. In this study we extend this analysis to in-clude 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 con-clude that it is possible to improve the performan...
It is well known that using high-locality representations is important for efficient evolutionary se...
The most salient feature of Grammatical Evolution (GE) is a procedure which maps genotypes to phenot...
Grammatical evolution (GE) is a recent grammar-based approach to genetic programming that allows dev...
We present an analysis of the genotype-phenotype map in Grammatical Evolution (GE). The standard map...
European Conference on Genetic Programming, Istanbul Turkey, 7-9 April, 2010We present an analysis o...
GECCO 2011, ACM Genetic and Evolutionary Computation Conference, Graduate Student Workshop, Dublin, ...
Grammatical evolution (GE) is a form of grammar-based genetic programming. A particular feature of G...
This paper investigates the locality of the genotypephenotype mapping (representation) used in gr...
Grammatical Evolution is an Evolutionary Algorithm which can evolve programs in any language describ...
In this report we analyse the properties of Structured Grammatical Evolu-tion (SGE), a new genotypic...
Evolvability is a measure of the ability of an Evolutionary Algorithm (EA) to improve the fitness of...
This paper explores an area within Evolutionary Computation called Grammatical Evolution [8]. This a...
We present Hierarchical Grammatical Evolution (HGE) and its variant Weighted HGE (WHGE), two novel g...
IEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, British Columbia, Canada, 16-21 Jul...
Paper presented at the 14th European Conference, EuroGP 2011, Torino, Italy, April 27-29, 2011We pre...
It is well known that using high-locality representations is important for efficient evolutionary se...
The most salient feature of Grammatical Evolution (GE) is a procedure which maps genotypes to phenot...
Grammatical evolution (GE) is a recent grammar-based approach to genetic programming that allows dev...
We present an analysis of the genotype-phenotype map in Grammatical Evolution (GE). The standard map...
European Conference on Genetic Programming, Istanbul Turkey, 7-9 April, 2010We present an analysis o...
GECCO 2011, ACM Genetic and Evolutionary Computation Conference, Graduate Student Workshop, Dublin, ...
Grammatical evolution (GE) is a form of grammar-based genetic programming. A particular feature of G...
This paper investigates the locality of the genotypephenotype mapping (representation) used in gr...
Grammatical Evolution is an Evolutionary Algorithm which can evolve programs in any language describ...
In this report we analyse the properties of Structured Grammatical Evolu-tion (SGE), a new genotypic...
Evolvability is a measure of the ability of an Evolutionary Algorithm (EA) to improve the fitness of...
This paper explores an area within Evolutionary Computation called Grammatical Evolution [8]. This a...
We present Hierarchical Grammatical Evolution (HGE) and its variant Weighted HGE (WHGE), two novel g...
IEEE Congress on Evolutionary Computation (CEC 2006), Vancouver, British Columbia, Canada, 16-21 Jul...
Paper presented at the 14th European Conference, EuroGP 2011, Torino, Italy, April 27-29, 2011We pre...
It is well known that using high-locality representations is important for efficient evolutionary se...
The most salient feature of Grammatical Evolution (GE) is a procedure which maps genotypes to phenot...
Grammatical evolution (GE) is a recent grammar-based approach to genetic programming that allows dev...