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Geometric semantic genetic programming with normalized and standardized random programs

Published:2024-02-08 Issue:1 Volume:25 Page:
ISSN:1389-2576
Container-title:Genetic Programming and Evolvable Machines
language:en
Short-container-title:Genet Program Evolvable Mach

Author:

Bakurov Illya,Muñoz Contreras José Manuel,Castelli Mauro,Rodrigues Nuno,Silva Sara,Trujillo Leonardo,Vanneschi Leonardo

Funder

Foundation for Science and Technology

Consejo Nacional de Ciencia y Tecnología

Foundation for Science and Technology, Portugal

Tecnológico Nacional de México

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10710-024-09479-1.pdf

Reference42 articles.

1. J. Albinati, G.l. Pappa, F.E. Otero et al., The effect of distinct geometric semantic crossover operators in regression problems, in Genetic Programming: 18th European Conference, EuroGP 2015, Copenhagen, Denmark, April 8–10, 2015, Proceedings 18 (Springer, 2015), pp. 3–15

2. I. Bakurov, L. Vanneschi, M. Castelli et al., Edda-v2—An improvement of the evolutionary demes despeciation algorithm, in Parallel Problem Solving from Nature—PPSN XV. ed. by A. Auger, C.M. Fonseca, N. Lourenço et al. (Springer International Publishing, Cham, 2018), pp. 185–196

3. I. Bakurov, M. Buzzelli, M. Castelli et al., General purpose optimization library (GPOL): a flexible and efficient multi-purpose optimization library in python. Appl. Sci. (2021). https://doi.org/10.3390/app11114774

4. I. Bakurov, M. Castelli, O. Gau et al., Genetic programming for stacked generalization. Swarm Evol. Comput. 65, 100913 (2021). https://doi.org/10.1016/j.swevo.2021.100913

5. I. Bakurov, M. Castelli, F. Fontanella et al., A novel binary classification approach based on geometric semantic genetic programming. Swarm Evol. Comput. 69, 101028 (2022). https://doi.org/10.1016/j.swevo.2021.101028

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1. SLIM_GSGP: The Non-bloating Geometric Semantic Genetic Programming;Lecture Notes in Computer Science;2024

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