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Publicação
Slim
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Resumo(s)
This poster presents Slim: an open-source Python library that provides the first ever framework for the Semantic Learning algorithm based on Inflate and deflate Mutation (SLIM-GSGP). Proposed by Vanneschi in 2024, SLIM-GSGP is a promising non-bloating variant of Geometric Semantic Genetic Programming (GSGP). The Slim library includes all existing SLIM-GSGP variants, as well as traditional GSGP and standard Genetic Programming (GP), facilitating comparative analysis and benchmarking. Additionally, Slim’s semi-modular architecture and parallel computation renders it not only fast but also user-friendly and easily extensible, thereby fostering progress in this emerging area of research.
Descrição
Rosenfeld, L., Farinati, D., Rasteiro, D., Pietropolli, G., Rebuli, K. B., Silva, S., & Vanneschi, L. (2024). Slim: a Python Library for the non-bloating SLIM-GSGP algorithm [poster]. 1. Poster session presented at Data Research Meetup by MagIC, Lisbon, Portugal. --- This work was supported by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS~(DOI: 10.54499/UIDB/04152/2020) and through the LASIGE R\&D Unit~(UIDB/00408/2020 and UIDP/00408/2020).