Zobrazeno 1 - 7
of 7
pro vyhledávání: '"den Hengst, Floris"'
Autor:
den Hengst, Floris, Otten, Martijn, Elbers, Paul, van Harmelen, Frank, François-Lavet, Vincent, Hoogendoorn, Mark
Publikováno v:
In Artificial Intelligence In Medicine January 2024 147
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Smit, Yannick, den Hengst, Floris, Bhulai, Sandjai, Mehdad, Ehsan, Nicosia, Giuseppe, Giuffrida, Giovanni, Ojha, Varun, La Malfa, Emanuele, La Malfa, Gabriele, Pardalos, Panos, Di Fatta, Giuseppe, Umeton, Renato
Publikováno v:
Machine Learning, Optimization, and Data Science ISBN: 9783031258909
Smit, Y, den Hengst, F, Bhulai, S & Mehdad, E 2023, Strategic Workforce Planning with Deep Reinforcement Learning . in G Nicosia, G Giuffrida, V Ojha, E La Malfa, G La Malfa, P Pardalos, G Di Fatta & R Umeton (eds), Machine Learning, Optimization, and Data Science : 8th International Conference, LOD 2022, Certosa di Pontignano, Italy, September 18–22, 2022, Revised Selected Papers, Part II . vol. 2, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13811 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 108-122, 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, held in conjunction with the 2nd Advanced Course and Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022, Certosa di Pontignano, Italy, 18/09/22 . https://doi.org/10.1007/978-3-031-25891-6_9
Machine Learning, Optimization, and Data Science: 8th International Conference, LOD 2022, Certosa di Pontignano, Italy, September 18–22, 2022, Revised Selected Papers, Part II, 2, 108-122
Smit, Y, den Hengst, F, Bhulai, S & Mehdad, E 2023, Strategic Workforce Planning with Deep Reinforcement Learning . in G Nicosia, G Giuffrida, V Ojha, E La Malfa, G La Malfa, P Pardalos, G Di Fatta & R Umeton (eds), Machine Learning, Optimization, and Data Science : 8th International Conference, LOD 2022, Certosa di Pontignano, Italy, September 18–22, 2022, Revised Selected Papers, Part II . vol. 2, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13811 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 108-122, 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, held in conjunction with the 2nd Advanced Course and Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022, Certosa di Pontignano, Italy, 18/09/22 . https://doi.org/10.1007/978-3-031-25891-6_9
Machine Learning, Optimization, and Data Science: 8th International Conference, LOD 2022, Certosa di Pontignano, Italy, September 18–22, 2022, Revised Selected Papers, Part II, 2, 108-122
This paper presents a simulation-optimization approach to strategic workforce planning based on deep reinforcement learning. A domain expert expresses the organization’s high-level, strategic workforce goals over the workforce composition. A policy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b76d3d591c8da511955840034719040
https://doi.org/10.1007/978-3-031-25891-6_9
https://doi.org/10.1007/978-3-031-25891-6_9
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
den Hengst, Floris, Francois-Lavet, Vincent, Hoogendoorn, Mark, van Harmelen, Frank, De Raedt, Luc
Publikováno v:
den Hengst, F, Francois-Lavet, V, Hoogendoorn, M & van Harmelen, F 2022, Reinforcement Learning with Option Machines . in L De Raedt (ed.), Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence . IJCAI International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence Organization, pp. 2909-2915, 31st International Joint Conference on Artificial Intelligence, IJCAI 2022, Vienna, Austria, 23/07/22 . https://doi.org/10.24963/ijcai.2022/403
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2909-2915
STARTPAGE=2909;ENDPAGE=2915;TITLE=Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2909-2915
STARTPAGE=2909;ENDPAGE=2915;TITLE=Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
Reinforcement learning (RL) is a powerful framework for learning complex behaviors, but lacks adoption in many settings due to sample size requirements. We introduce a framework for increasing sample efficiency of RL algorithms. Our approach focuses
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20ab5b44dc8c9533ca867a559e73d7b1
https://hdl.handle.net/1871.1/61ccaa2a-ed48-426b-b47b-8a7e58aff4bd
https://hdl.handle.net/1871.1/61ccaa2a-ed48-426b-b47b-8a7e58aff4bd
Autor:
Den Hengst, Floris, Hoogendoorn, Mark, Van Harmelen, Frank, Bosman, Joost, Barnaghi, Payam, Gottlob, Georg, Manolopoulos, Yannis, Tzouramanis, Theodoros, Vakali, Athena
Publikováno v:
Den Hengst, F, Hoogendoorn, M, Van Harmelen, F & Bosman, J 2019, Reinforcement learning for personalized dialogue management . in P Barnaghi, G Gottlob, Y Manolopoulos, T Tzouramanis & A Vakali (eds), 2WI '19: IEEE/WIC/ACM International Conference on Web Intelligence : Proceedings . Association for Computing Machinery, Inc, pp. 59-67, 19th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2019, Thessaloniki, Greece, 13/10/19 . https://doi.org/10.1145/3350546.3352501
2WI '19: IEEE/WIC/ACM International Conference on Web Intelligence: Proceedings, 59-67
STARTPAGE=59;ENDPAGE=67;TITLE=2WI '19: IEEE/WIC/ACM International Conference on Web Intelligence
WI
2WI '19: IEEE/WIC/ACM International Conference on Web Intelligence: Proceedings, 59-67
STARTPAGE=59;ENDPAGE=67;TITLE=2WI '19: IEEE/WIC/ACM International Conference on Web Intelligence
WI
Language systems have been of great interest to the research community and have recently reached the mass market through various assistant platforms on the web. Reinforcement Learning methods that optimize dialogue policies have seen successes in pas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b37e7e966aa32a76c60a6147baaa472b
https://hdl.handle.net/1871.1/faa3b7ce-d404-42d1-bd53-cbe1de2cc707
https://hdl.handle.net/1871.1/faa3b7ce-d404-42d1-bd53-cbe1de2cc707
Publikováno v:
Data Science; November 2020, Vol. 3 Issue: 2 p107-147, 41p