We report a series of experiments within a multiobjective genetic programming (GP) framework using semantic-based local GP search. We have made comparison with the Random Desired Operator (RDO) of Pawlak et al. and find that a standard generational GP followed by a carefully-designed single-objective GP implementing semantic-based local search yields results statistically comparable to those obtained with the RDO operator. The trees obtained with our GP-based local search technique are, however, around half the size of the trees resulting from the use of the RDO
One sub-field of Genetic Programming (GP) which has gained recent interest is semantic GP, in which ...
Abstract. In this paper, we use multi-objective techniques to compare different genetic programming ...
Genetic programming (GP) is applied to a multobjective optimisation problem and the advantages of ...
We report a series of experiments that use semantic-based local search within a multiobjective genet...
4siIn this paper we continue the investigation of the effect of local search in geometric semantic g...
Semantics has become a key topic of research in Genetic Programming (GP). Semantics refers to the ou...
Traditional Genetic Programming (GP) searches the space of functions/programs by using search operat...
The development and optimisation of programs through search is a growing application area for comput...
Paper presented at the ACM Genetic and Evolutionary Computation Conference, GECCO 2011, 12-16 July, ...
Best Paper Award in the GP track - see http://www.sigevo.org/gecco-2015/papers.htmlInternational aud...
Abstract. Traditional Genetic Programming (GP) searches the space of functions/programs by using sea...
The study of semantics in Genetic Programming (GP) has increased dramatically over the last years du...
peer reviewedAchieving a balance between the exploration and exploitation capabilities of genetic al...
Achieving a balance between the exploration and exploitation capabilities of genetic algorithms is a...
3siGeometric Semantic Genetic Programming (GSGP) is a recently introduced framework to design domain...
One sub-field of Genetic Programming (GP) which has gained recent interest is semantic GP, in which ...
Abstract. In this paper, we use multi-objective techniques to compare different genetic programming ...
Genetic programming (GP) is applied to a multobjective optimisation problem and the advantages of ...
We report a series of experiments that use semantic-based local search within a multiobjective genet...
4siIn this paper we continue the investigation of the effect of local search in geometric semantic g...
Semantics has become a key topic of research in Genetic Programming (GP). Semantics refers to the ou...
Traditional Genetic Programming (GP) searches the space of functions/programs by using search operat...
The development and optimisation of programs through search is a growing application area for comput...
Paper presented at the ACM Genetic and Evolutionary Computation Conference, GECCO 2011, 12-16 July, ...
Best Paper Award in the GP track - see http://www.sigevo.org/gecco-2015/papers.htmlInternational aud...
Abstract. Traditional Genetic Programming (GP) searches the space of functions/programs by using sea...
The study of semantics in Genetic Programming (GP) has increased dramatically over the last years du...
peer reviewedAchieving a balance between the exploration and exploitation capabilities of genetic al...
Achieving a balance between the exploration and exploitation capabilities of genetic algorithms is a...
3siGeometric Semantic Genetic Programming (GSGP) is a recently introduced framework to design domain...
One sub-field of Genetic Programming (GP) which has gained recent interest is semantic GP, in which ...
Abstract. In this paper, we use multi-objective techniques to compare different genetic programming ...
Genetic programming (GP) is applied to a multobjective optimisation problem and the advantages of ...