Edgar Galván López

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We investigate the effects of semantically-based crossover operators in Genetic Programming, applied to real-valued symbolic regression problems. We propose two new relations derived from the semantic distance between subtrees, known as Semantic Equivalence and Semantic Similarity. These relations are used to guide variants of the crossover operator,(More)
The effects of neutrality on evolutionary search have been considered in a number of studies, the results of which, however, have been contradictory. Some have found neutrality to be beneficial to aid evolution whereas others have argued that neutrality in the evolutionary process is useless. We believe that this confusion is due to several reasons: many(More)
The effects of neutrality on evolutionary search have been considered in a number of interesting studies, the results of which, however , have been contradictory. We believe that this confusion is due to several reasons. In this paper, we shed some light on neutrality by addressing these problems. That is, we use the simplest possible definition of(More)
The effects of neutrality on evolutionary search are not fully understood. In this paper we make an effort to shed some light on how and why bit-wise neutrality - an important form of neutrality induced by a genotype-phenotype map where each phenotypic bit is obtained by transforming a group of genotypic bits via an encoding function - influences the(More)
Locality - how well neighbouring genotypes correspond to neighbouring phenotypes - has been defined as a key element affecting how Evolutionary Computation systems explore and exploit the search space. Locality has been studied empirically using the typical Genetic Algorithm (GA) representation (i.e., bitstrings), and it has been argued that locality plays(More)
A mapping is local if it preserves neighbourhood. In Evolutionary Computation , locality is generally described as the property that neighbouring genotypes correspond to neighbouring phenotypes. A representation has high locality if most genotypic neighbours are mapped to phenotypic neighbours. Locality is seen as a key element in performing effective(More)
In this paper we propose a new method for implementing the cross-over operator in Genetic Programming (GP) called Semantic Similarity based Crossover (SSC). This new operator is inspired by Semantic Aware Crossover (SAC) [20]. SSC extends SAC by adding semantics to control the change of the semantics of the individuals during the evolutionary process. The(More)
— A key indicator of problem difficulty in evolutionary computation problems is the landscape's locality, that is whether the genotype-phenotype mapping preserves neighbourhood. In genetic programming the genotype and phenotype are not distinct, but the locality of the genotype-fitness mapping is of interest. In this paper we extend the original standard(More)
— In real-world problems with candidate solutions that are very expensive to evaluate, Surrogate Models (SMs) mimic the behaviour of the simulation model as closely as possible while being computationally cheaper to evaluate. Due to their nature, SMs can be seen as heuristics that can help to estimate the fitness of a candidate solution without having to(More)