Created by W.Langdon from gp-bibliography.bib Revision:1.8051
we propose Probabilistic Grammatical Evolution (PGE), which introduces a new genotypic representation and new mapping mechanism for GE. Specifically, we resort to a Probabilistic Context-Free Grammar (PCFG) where its probabilities are adapted during the evolutionary process, taking into account the productions chosen to construct the fittest individual. The genotype is a list of real values, where each value represents the likelihood of selecting a derivation rule. We evaluate the performance of PGE in two regression problems and compare it with GE and Structured Grammatical Evolution (SGE).
The results show that PGE has a better performance than GE, with statistically significant differences, and achieved similar performance when comparing with SGE.",
https://estagios.dei.uc.pt/cursos/mei/ano-lectivo-2020-2021/proposta-com-alunos-identificados/?idestagio=3902
http://www.evostar.org/2021/eurogp/ Part of \cite{Hu:2021:GP} EuroGP'2021 held in conjunction with EvoCOP2021, EvoMusArt2021 and EvoApplications2021",
Genetic Programming entries for Jessica Megane Nuno Lourenco Penousal Machado