Please use this identifier to cite or link to this item: http://infotec.repositorioinstitucional.mx/jspui/handle/1027/217
Semantic Genetic Programming Operators Based on Projections in the Projections in the Phenotype Space
ERIC SADIT TELLEZ AVILA
SABINO MIRANDA JIMENEZ
MARIO GRAFF GUERRERO
Elio Atenógenes Villaseñor García
Acceso Abierto
Atribución-NoComercial-SinDerivadas
Tecnologías de la Información y Comunicación
In the Genetic Programming (GP) community there has been a great interest in developing semantic genetic operators. These type of operators use information of the phenotype to create ospring. The most recent approaches of semantic GP include the GP framework based on the alignment of error space, the geometric semantic genetic operators, and backpropagation genetic operators. Our contribution proposes two semantic operators based on projections in the phenotype space. The proposed operators have the characteristic, by construction, that the ospring's tness is as at least as good as the tness of the best parent; using as tness the euclidean distance. The semantic operators proposed increment the learning capabilities of GP. These operators are compared against a traditional GP and Geometric Semantic GP in the Human oral bioavailability regression problem and 13 classication problems. The results show that a GP system with our novel semantic operators has the best performance in the training phase in all the problems tested.
Research in Computing Science 94
2015
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