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A Generic Framework for Building Dispersion Operators in the Semantic Space

Oliveira, Luiz O.V.B. and Otero, Fernando E.B. and Pappa, Gisele L. (2018) A Generic Framework for Building Dispersion Operators in the Semantic Space. In: Genetic Programming Theory and Practice XIV. Genetic and Evolutionary Computation . Springer, pp. 179-195. ISBN 978-3-319-97088-2. E-ISBN 978-3-319-97087-5. (doi:10.1007/978-3-319-97088-2_12) (KAR id:59297)


This chapter proposes a generic framework to build geometric dispersion (GD) operators for Geometric Semantic Genetic Programming in the context of symbolic regression, followed by two concrete instantiations of the framework: a multiplicative geometric dispersion operator and an additive geometric dispersion operator. These operators move individuals in the semantic space in order to balance the population around the target output in each dimension, with the objective of expanding the convex hull defined by the population to include the desired output vector. An experimental analysis was conducted in a testbed composed of sixteen datasets showing that dispersion operators can improve GSGP search and that the multiplicative version of the operator is overall better than the additive version.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-319-97088-2_12
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Fernando Otero
Date Deposited: 30 Nov 2016 13:49 UTC
Last Modified: 09 Dec 2022 03:41 UTC
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