Zobrazeno 1 - 10 of 190 pro vyhledávání: '"Spaan, M.T.J."'
1
Large-scale collaborative vehicle routing
Autor: Los, J., Schulte, F., Gansterer, Margaretha, Hartl, Richard F., Spaan, M.T.J., Negenborn, R.R.
Publikováno v: Annals of Operations Research
Carriers can remarkably reduce transportation costs and emissions when they collaborate, for example through a platform. Such gains, however, have only been investigated for relatively small problem instances with low numbers of carriers. We develop
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90f31ede400198f33666a3ce3d2a100b
https://doi.org/10.1007/s10479-021-04504-3
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2
Speeding up Deep Reinforcement Learning through Influence-Augmented Local Simulators
Autor: Suau, M., He, J., Spaan, M.T.J., Oliehoek, F.A.
Publikováno v: International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022
Learning effective policies for real-world problems is still an open challenge for the field of reinforcement learning (RL). The main limitation being the amount of data needed and the pace at which that data can be obtained. In this paper, we study
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::4fc7d3e18ab657b39042ed957d59237f
http://resolver.tudelft.nl/uuid:0307bd82-46f0-4387-a805-53bf44c572b0
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3
Abstraction-Refinement for Hierarchical Probabilistic Models
Autor: Junges, Sebastian, Spaan, M.T.J., Shoham, Sharon, Vizel, Yakir
Publikováno v: Shoham, S.; Vizel, Y. (ed.), Computer Aided Verification:34th International Conference, CAV 2022, Haifa, Israel, August 7–10, 2022, Proceedings, Part I, 102-123. Cham : Springer International Publishing
STARTPAGE=102;ENDPAGE=123;ISSN=0302-9743;TITLE=Shoham, S.; Vizel, Y. (ed.), Computer Aided Verification:34th International Conference, CAV 2022, Haifa, Israel, August 7–10, 2022, Proceedings, Part I
Computer Aided Verification-34th International Conference, CAV 2022, Proceedings
ISSUE=Part 1;TITLE=Computer Aided Verification-34th International Conference, CAV 2022, Proceedings
Computer Aided Verification ISBN: 9783031131844
Markov decision processes are a ubiquitous formalism for modelling systems with non-deterministic and probabilistic behavior. Verification of these models is subject to the famous state space explosion problem. We alleviate this problem by exploiting
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95e23e2805f174a689473f80422c1e35
http://resolver.tudelft.nl/uuid:e51518bc-269d-4b2c-a191-917d4f4e1144
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4
Strategic Bidding in Decentralized Collaborative Vehicle Routing
Autor: Los, J., Schulte, F., Spaan, M.T.J., Negenborn, R.R., Freitag, Michael, Kinra, Aseem, Kotzab, Herbert, Megow, Nicole
Publikováno v: Dynamics in Logistics: Proceedings of the 8th International Conference LDIC 2022, Bremen, Germany
Dynamics in Logistics
Dynamics in Logistics ISBN: 9783031053580
Collaboration in transportation is important to reduce costs and emissions, but carriers may have incentives to bid strategically in decentralized auction systems. We investigate what the effect of the auction strategy is on the possible cheating ben
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::875bc5889eee9b19e1bf04a04ba24201
http://resolver.tudelft.nl/uuid:359b2a96-a7de-407d-a736-694335e1dc11
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6
Refined Risk Management in Safe Reinforcement Learning with a Distributional Safety Critic
Autor: Yang, Q., Simão, T. D., Tindemans, Simon H., Spaan, M.T.J., Bossens, David, Giguere, Stephen, Bloem, Roderick, Koenighofer, Bettina
Publikováno v: Safe RL Workshop at IJCAI 2022
Safety is critical to broadening the real-world use of reinforcement learning (RL). Modeling the safety aspects using a safety-cost signal separate from the reward is becoming standard practice, since it avoids the problem of finding a good balance b
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::2ae2ed0dd9886ab6885f5d2a784ee67c
http://resolver.tudelft.nl/uuid:7cfa2a33-6ad7-458a-827d-06e9d57a969c
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7
Abstraction-Refinement for Hierarchical Probabilistic Models
Autor: Junges, S., Spaan, M.T.J.
Publikováno v: Shoham, S.; Vizel, Y. (ed.), Computer Aided Verification:34th International Conference, CAV 2022, Haifa, Israel, August 7–10, 2022, Proceedings, Part I, pp. 102-123
Contains fulltext : 282987.pdf (Publisher’s version ) (Open Access) CAV 2022
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https://repository.ubn.ru.nl/handle/2066/282987
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8
Influence-Augmented Local Simulators: a Scalable Solution for Fast Deep RL in Large Networked Systems
Autor: Suau de Castro, M., He, J., Spaan, M.T.J., Oliehoek, F.A., Chaudhuri, K., Jegelka, S., Song, L., Szepesvari, C., Niu, G., Sabato, S.
Publikováno v: Proceedings of the 39th International Conference on Machine Learning, 162
Learning effective policies for real-world problems is still an open challenge for the field of reinforcement learning (RL). The main limitation being the amount of data needed and the pace at which that data can be obtained. In this paper, we study
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::64c15b37f07a967ff1857af5d9157cb6
http://resolver.tudelft.nl/uuid:ec39b987-ac99-4fa3-92f4-f25006505d50
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9
PEBL: Pessimistic Ensembles for Offline Deep Reinforcement Learning
Autor: Smit, Jordi, Ponnambalam, C.T., Spaan, M.T.J., Oliehoek, F.A.
Publikováno v: Robust and Reliable Autonomy in the Wild Workshop at the 30th International Joint Conference of Artificial Intelligence
Offline reinforcement learning (RL), or learning from a fixed data set, is an attractive alternative to online RL. Offline RL promises to address the cost and safety implications of tak- ing numerous random or bad actions online, a crucial aspect of
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::53b519b8130b06db6c31af4e829aafe6
http://resolver.tudelft.nl/uuid:2053b579-a663-4def-ad25-4bedad0169be
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10
AlwaysSafe: Reinforcement Learning without Safety Constraint Violations during Training
Autor: Simão, T.D., Jansen, N., Spaan, M.T.J., Dignum, F.
Publikováno v: Dignum, F. (ed.), AAMAS 2021: Proceedings of the 20th International Conference on Autonomous Agentsand Multiagent Systems (AAMAS 2021), Online, May 3–7, 2021, IFAAMAS. Online, 1226-1235. New York : ACM
STARTPAGE=1226;ENDPAGE=1235;TITLE=Dignum, F. (ed.), AAMAS 2021: Proceedings of the 20th International Conference on Autonomous Agentsand Multiagent Systems (AAMAS 2021), Online, May 3–7, 2021, IFAAMAS.
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::94c4d345fb7c7ee32e780b7b5caa1d19
http://hdl.handle.net/2066/233934
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