In this paper we continue the investigation of the effect of local search in geometric semantic genetic programming (GSGP), with the introduction of a new general local search operator that can be easily customized. We show that it is able to obtain results on par with the current best-performing GSGP with local search and, in most cases, better than standard GSGP.

Castelli, M., Manzoni, L., Mariot, L., Saletta, M. (2019). Extending local search in geometric semantic genetic programming. In Progress in Artificial Intelligence (pp.775-787). Springer Verlag [10.1007/978-3-030-30241-2_64].

Extending local search in geometric semantic genetic programming

Manzoni, L;Mariot, L
;
Saletta, M
2019

Abstract

In this paper we continue the investigation of the effect of local search in geometric semantic genetic programming (GSGP), with the introduction of a new general local search operator that can be easily customized. We show that it is able to obtain results on par with the current best-performing GSGP with local search and, in most cases, better than standard GSGP.
paper
geometric semantic genetic programming, local search, symbolic regression;
English
EPIA Conference on Artificial Intelligence, EPIA 2019 - 3 September 2019 through 6 September 2019
2019
Moura Oliveira, P; Novais, P; Reis, LP
Progress in Artificial Intelligence
978-303030240-5
2019
11804
775
787
none
Castelli, M., Manzoni, L., Mariot, L., Saletta, M. (2019). Extending local search in geometric semantic genetic programming. In Progress in Artificial Intelligence (pp.775-787). Springer Verlag [10.1007/978-3-030-30241-2_64].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/255396
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