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A recent study showed that GSGP can be hybridized with a standard gradient-based optimized, Adam, commonly used in training artificial neural networks.We expand upon that work by considering more gradient-based optimizers, a deeper investigation of their parameters, how the hybridization is performed, and a more comprehensive set of benchmark problems. With the correct choice of hyperparameters, this hybridization improves the performances of GSGP and allows it to reach the same fitness values with fewer fitness evaluations.<\/jats:p>","DOI":"10.1007\/s10710-023-09463-1","type":"journal-article","created":{"date-parts":[[2023,10,28]],"date-time":"2023-10-28T14:01:52Z","timestamp":1698501712000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["On the hybridization of geometric semantic GP with gradient-based optimizers"],"prefix":"10.1007","volume":"24","author":[{"given":"Gloria","family":"Pietropolli","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luca","family":"Manzoni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessia","family":"Paoletti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mauro","family":"Castelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,10,28]]},"reference":[{"key":"9463_CR1","volume-title":"Genetic Programming: On the Programming of Computers by Means of Natural Selection","author":"JR Koza","year":"1992","unstructured":"J.R. 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