Výsledky vyhledávání - dynamic algorithm configuration

On the Importance of Reward Design in Reinforcement Learning-based Dynamic Algorithm Configuration: A Case Study on OneMax with (1+(λ,λ))-GA

Autoři: Nguyen, Tai Le, Phong Biedenkapp, André a další

Přispěvatelé: Nguyen, Tai Le, Phong Biedenkapp, André a další

Zdroj: Proceedings of the Genetic and Evolutionary Computation Conference. :1162-1171

Témata: Machine Learning, FOS: Computer and information sciences, Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), [INFO] Computer Science [cs], Machine Learning (cs.LG)

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2502.20265
https://hal.science/hal-05171390v1/document
https://doi.org/10.1145/3712256.3726395
https://hal.science/hal-05171390v1

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

Autoři: Carolin Benjamins Gjorgjina Cenikj Ana Nikolikj a další

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

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

Popis souboru: text/url; application/pdf

Přístupová 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

Search Trajectory Network-Enhanced Multi-Objective Dynamic Algorithm Configuration

Autoři: Reijnen, Robbert Bukhsh, Zaharah Lau, Hoong Chuin a další

Zdroj: ECAI 2025. 413

Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization

Autoři: Reijnen, Robbert Wu, Yaoxin Bukhsh, Zaharah a další

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2505.16471

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

Reinforcement learning strategies for dynamic configuration of metaheuristics

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

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

Zdroj: urn:tid:203734378

Témata: 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 souboru: application/pdf

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

Metamodel-based dynamic algorithm configuration using artificial neural networks

Autoři: Dunke, Fabian Nickel, Stefan

Zdroj: International Journal of General Systems. 53:41-71

Témata: ddc:330, Economics

Theory-inspired parameter control benchmarks for dynamic algorithm configuration

Autoři: Biedenkapp, André Dang, Nguyen Krejca, Martin a další

Přispěvatelé: Biedenkapp, André Dang, Nguyen Krejca, Martin a další

Zdroj: Proceedings of the Genetic and Evolutionary Computation Conference. :766-775

Témata: MCC, QA75, [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], FOS: Computer and information sciences, Computer Science - Machine Learning, QA75 Electronic computers. Computer science, [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], Computer Science - Neural and Evolutionary Computing, 02 engineering and technology, NS, NIS, Machine Learning (cs.LG), 0202 electrical engineering, electronic engineering, information engineering, Neural and Evolutionary Computing (cs.NE)

Popis souboru: application/pdf

Přístupová URL adresa: http://arxiv.org/abs/2202.03259
https://hal.science/hal-03646966v1
https://doi.org/10.1145/3512290.3528846
https://hal.science/hal-03646966v1/document
https://dl.acm.org/doi/proceedings/10.1145/3512290
https://hdl.handle.net/10023/26886

From benchmarking optimization heuristics to dynamic algorithm configuration

Autoři: Vermetten, D.L. Bäck, T.H.W. Doerr, C. a další

Přispěvatelé: Vermetten, D.L. Bäck, T.H.W. Doerr, C. a další

Témata: Optimization, Benchmarking, Dynamic algorithm selection, Modular Algorithms, Black-box, Evolutionary Algorithms, Algorithm configuration, Exploratory Landscape Analysis

Popis souboru: application/pdf

Přístupová URL adresa: https://hdl.handle.net/1887/4180395

Automated Dynamic Algorithm Configuration

Autoři: Adriansen, Steven Biedenkapp, André Shala, Gresa a další

Zdroj: Journal of Artificial Intelligence Research. 75:1633-1699

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, Computer Science - Neural and Evolutionary Computing, Neural and Evolutionary Computing (cs.NE), 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2205.13881

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

Autoři: Benjamins, Carolin Cenikj, Gjorgjina Nikolikj, Ana a další

Témata: Computer Science - Machine Learning, text

URL: http://arxiv.org/abs/2407.13513

A Dynamic Algorithm Configuration Framework Using Combinatorial Problem Features and Reinforcement Learning

Autoři: Elmar Steiner Ulrich Pferschy

Zdroj: Lecture Notes in Computer Science ISBN: 9783031629211

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

Autoři: Benjamins, Carolin Cenikj, Gjorgjina Nikolikj, Ana a další

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

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

Popis souboru: 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

Dostupnost: 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

Development of algorithms for enhancing numerical simulations in CFD & HT: conjugate heat transfer, moving bodies, indoor air quality, and thermal energy storage

Autoři: Vera i Fernández, Jordi

Přispěvatelé: University/Department: Universitat Politècnica de Catalunya. Departament de Màquines i Motors Tèrmics

Thesis Advisors: Oliva Llena, Asensio, Pérez Segarra, Carlos David

Zdroj: TDX (Tesis Doctorals en Xarxa)

Témata: Computational Fluid Dynamics and Heat Transfer (CFD & HT), Immersed Boundary Method (IBM), Sliding Meshes, Moving Bodies, Indoor Air Quality, Infection Probability, Thermal Energy Storage (TES), Thermocline, Àrees temàtiques de la UPC::Enginyeria mecànica, Àrees temàtiques de la UPC::Energies, 621 - Enginyeria mecànica en general. Tecnologia nuclear. Electrotècnia. Maquinària, 620 - Assaig de materials. Material comercials. Economia de l'energia

Popis souboru: application/pdf

Přístupová URL adresa: http://hdl.handle.net/10803/693918
https://dx.doi.org/10.5821/dissertation-2117-425645

Dynamic Algorithm Configuration for Machine Scheduling Using Deep Reinforcement Learning

Autoři: Reijnen, Robbert Victor Jacobus

Zdroj: Reijnen, R V J 2025, 'Dynamic Algorithm Configuration for Machine Scheduling Using Deep Reinforcement Learning', Doctor of Philosophy, Industrial Engineering and Innovation Sciences, Eindhoven.

Popis souboru: application/pdf

Relation: info:eu-repo/semantics/altIdentifier/isbn/978-90-386-6486-6

Dostupnost: https://research.tue.nl/en/publications/836f108e-28dc-4b1b-b7b9-1ad6bc18da52
https://pure.tue.nl/ws/files/367900792/20251013_Reijnen_hf.pdf

Learning Heuristic Selection with Dynamic Algorithm Configuration

Autoři: Speck, David Biedenkapp, André Hutter, Frank a další

Zdroj: Proceedings of the International Conference on Automated Planning and Scheduling. 31:597-605

Témata: FOS: Computer and information sciences, Computer Science - Machine Learning, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence, 0202 electrical engineering, electronic engineering, information engineering, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Machine Learning (cs.LG)

Přístupová URL adresa: http://arxiv.org/abs/2006.08246

DACBench: A Benchmark Library for Dynamic Algorithm Configuration

Autoři: Theresa Eimer Steven Adriansen Frank Hutter a další

Zdroj: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. :1668-1674

Témata: FOS: Computer and information sciences, Artificial Intelligence (cs.AI), Computer Science - Artificial Intelligence

Přístupová URL adresa: https://www.ijcai.org/proceedings/2021/0230.pdf
http://arxiv.org/abs/2105.08541
https://dblp.uni-trier.de/db/conf/ijcai/ijcai2021.html#EimerBRAHL21
https://doi.org/10.24963/ijcai.2021/230
https://www.ijcai.org/proceedings/2021/0230.pdf
https://www.ijcai.org/proceedings/2021/230

Sequential Multi-Agent Dynamic Algorithm Configuration

Autoři: Lu, Chen Xue, Ke Yuan, Lei a další

Témata: Machine Learning, Neural and Evolutionary Computing

Relation: http://arxiv.org/abs/2510.23535

Dostupnost: http://arxiv.org/abs/2510.23535

Multi-agent Dynamic Algorithm Configuration

Autoři: Xue, Ke Xu, Jiacheng Yuan, Lei a další

Témata: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Multiagent Systems, Computer Science - Neural and Evolutionary Computing, text

URL: http://arxiv.org/abs/2210.06835

Automated Dynamic Algorithm Configuration

Autoři: Adriaensen, Steven Biedenkapp, André Shala, Gresa a další

Témata: Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing, text

URL: http://arxiv.org/abs/2205.13881

DACBench: A Benchmark Library for Dynamic Algorithm Configuration

Autoři: Eimer, Theresa Biedenkapp, André Reimer, Maximilian a další

Témata: Computer Science - Artificial Intelligence, text

URL: http://arxiv.org/abs/2105.08541