Geometric semantic genetic programming with normalized and standardized random programs

Geometric semantic genetic programming (GSGP) represents one of the most promising developments in the area of evolutionary computation (EC) in the last decade. The results achieved by incorporating semantic awareness in the evolutionary process demonstrate the impact that geometric semantic operato...

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Vydáno v:	Genetic programming and evolvable machines Ročník 25; číslo 1
Hlavní autoři:	Bakurov, Illya, Muñoz Contreras, José Manuel, Castelli, Mauro, Rodrigues, Nuno, Silva, Sara, Trujillo, Leonardo, Vanneschi, Leonardo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.06.2024 Springer Nature B.V
Témata:	Artificial Intelligence Biomedical Engineering and Bioengineering Compilers Computer Science Deep learning Electrical Engineering Evolutionary computation Genetic algorithms Interpreters Operators (mathematics) Programming Languages Programming Techniques Semantics Software Engineering/Programming and Operating Systems Standardization Geometric semantic mutation Internal covariate shift Sigmoid distribution bias Model simplification
ISSN:	1389-2576, 1573-7632
On-line přístup:	Získat plný text
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