Genetic Programming: Semantic point mutation operator based on the partial derivative error

Created by W.Langdon from gp-bibliography.bib Revision:1.7964

@InProceedings{Graff:2014:ROPEC,

• author = "Mario Graff and Juan J. Flores and Jose {Ortiz Bejar}",
• booktitle = "IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC 2014)",
• title = "Genetic Programming: Semantic point mutation operator based on the partial derivative error",
• year = "2014",
• month = nov,
• abstract = "There is a great interest in the Genetic Programming (GP) community to develop semantic genetic operators. Most recent approaches includes the genetic programming framework for symbolic regression called Error Space Alignment GP, the geometric semantic operators, and our previous work the semantic crossover based on the partial derivative error. To the best of our knowledge, there has not been a semantic genetic operator similar to the point mutation. In this contribution, we start filling this gap by proposing a semantic point mutation based on the derivative of the error. This novel operator complements our previous semantic crossover and, as the results show, there is an improvement in performance when this novel operator is used, and, furthermore, the best performance in our setting is the system that uses the semantic crossover and the semantic point mutation.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/ROPEC.2014.7036344",
• notes = "Also known as \cite{7036344}",

}

Genetic Programming entries for Mario Graff Guerrero Juan J Flores Jose Ortiz Bejar

Citations