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A comparison between Geometric Semantic GP and Cartesian GP for Boolean functions learning?

Mambrini Andrea
•
Manzoni Luca
2014
  • conference object

Abstract
Geometric Semantic Genetic Programming (GSGP) is a recently defined form of Genetic Programming (GP) that has shown promising results on single output Boolean problems when compared with standard tree-based GP. In this paper we compare GSGP with Cartesian GP (CGP) on comprehensive set of Boolean benchmarks, consisting of both single and multiple outputs Boolean problems. The results obtained show that GSGP outperforms also CGP, confirming the efficacy of GSGP in solving Boolean problems.
DOI
10.1145/2598394.2598475
Archivio
http://hdl.handle.net/11368/2947960
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-84905644410
Diritti
metadata only access
Soggetti
  • Boolean function

  • Cartesian genetic pro...

  • Geometric Semantic Ge...

Scopus© citazioni
5
Data di acquisizione
Jun 14, 2022
Vedi dettagli
Visualizzazioni
3
Data di acquisizione
Apr 19, 2024
Vedi dettagli
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