Výsledky vyhľadávania - "Dynamic algorithm configuration"

Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization: improving generalization

Autori: Carolin Benjamins Gjorgjina Cenikj Ana Nikolikj a ďalší

Zdroj: Proceedings of the Genetic and Evolutionary Computation Conference Companion. :563-566

Predmety: izbira algoritmov, FOS: Computer and information sciences, reinforcement learning, instance selection, Computer Science - Machine Learning, dynamic algorithm configuration, generalization, Machine Learning (cs.LG)

Popis súboru: text/url; application/pdf

Prístupová URL adresa: http://arxiv.org/abs/2407.13513
https://dirros.openscience.si/IzpisGradiva.php?id=20445
https://doi.org/10.1145/3638530.3654291
https://hdl.handle.net/20.500.12556/DiRROS-20445

Estratégias de aprendizagem por reforço para configuração dinâmica de meta-heurísticas

Reinforcement learning strategies for dynamic configuration of metaheuristics

Autori: Oliveira, Vítor José Henriques Pinto, Tiago Manuel Campelos Ferreira Ramos, Carlos Fernando da Silva a ďalší

Prispievatelia: Oliveira, Vítor José Henriques Pinto, Tiago Manuel Campelos Ferreira Ramos, Carlos Fernando da Silva a ďalší

Zdroj: urn:tid:203734378

Predmety: Algoritmo genético, Aprendizagem máquina, Aprendizagem por reforço, Configuração dinâmica de algoritmos, DAC, Otimização por enxame de partículas, SARSA, Deep-SARSA, Dynamic algorithm configuration, Reinforcement learning, Genetic algorithm, Particle swarm optimization, Machine learning

Popis súboru: application/pdf

Dostupnosť: http://hdl.handle.net/10400.22/26902

Multi-parameter control for the (1+(λ,λ))-GA on OneMax via deep reinforcement learning

Autori: Nguyen, Tai Le, Phong Doerr, Carola a ďalší

Zdroj: Nguyen , T , Le , P , Doerr , C & Dang , N 2025 , Multi-parameter control for the (1+(λ,λ))-GA on OneMax via deep reinforcement learning . in Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic Algorithms . ACM , Conference on Foundations of Genetic Algorithms , Leiden , Netherlands , 27/08/25 . https://doi.org/10.1145/3729878.3746703

Predmety: Deep reinforcement learning, Dynamic algorithm configuration, Optimisation

Dostupnosť: https://research-portal.st-andrews.ac.uk/en/publications/f6c918e8-0d5a-45b5-ab32-78022b6d065a
https://doi.org/10.1145/3729878.3746703
https://dl.acm.org/conference/foga
https://arxiv.org/abs/2505.12982

Instance selection for dynamic algorithm configuration with reinforcement learning ; Instance selection for dynamic algorithm configuration with reinforcement learning: improving generalization

Autori: Benjamins, Carolin Cenikj, Gjorgjina Nikolikj, Ana a ďalší

Zdroj: GECCO'24 companion, pp. 563-566, 2024. ; ISBN: 979-8-4007-0495-6 ; ZDA

Predmety: dynamic algorithm configuration, reinforcement learning, instance selection, generalization, izbira algoritmov, info:eu-repo/classification/udc/004.8

Popis súboru: text/url; application/pdf

Relation: info:eu-repo/grantAgreement/ARRS//P2-0098; info:eu-repo/grantAgreement/ARRS//J2-4460; info:eu-repo/grantAgreement/ARRS/young researcher grant/PR-12393; info:eu-repo/grantAgreement/ARRS/young researcher grant/PR-12897; info:eu-repo/grantAgreement/other//57654659; https://dirros.openscience.si/IzpisGradiva.php?id=20445; https://dirros.openscience.si/Dokument.php?id=28794&dn=; https://dirros.openscience.si/Dokument.php?id=28799&dn=; https://plus.cobiss.net/cobiss/si/sl/bib/206992131

Dostupnosť: https://dirros.openscience.si/IzpisGradiva.php?id=20445
https://dirros.openscience.si/Dokument.php?id=28794&dn=
https://dirros.openscience.si/Dokument.php?id=28799&dn=
https://plus.cobiss.net/cobiss/si/sl/bib/206992131
https://hdl.handle.net/20.500.12556/DiRROS-20445

Estratégias de aprendizagem por reforço para configuração dinâmica de meta-heurísticas ; Reinforcement learning strategies for dynamic configuration of metaheuristics

Autori: Oliveira, Vítor José Henriques Pinto, Tiago Manuel Campelos Ferreira Ramos, Carlos Fernando da Silva

Prispievatelia: Oliveira, Vítor José Henriques Pinto, Tiago Manuel Campelos Ferreira Ramos, Carlos Fernando da Silva

Predmety: Algoritmo genético, Aprendizagem máquina, Aprendizagem por reforço, Configuração dinâmica de algoritmos, DAC, Otimização por enxame de partículas, SARSA, Deep-SARSA, Dynamic algorithm configuration, Reinforcement learning, Genetic algorithm, Particle swarm optimization, Machine learning, Domínio/Área Científica::Engenharia e Tecnologia

Relation: http://hdl.handle.net/10400.22/26902; 203734378

Dostupnosť: http://hdl.handle.net/10400.22/26902