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ORCIDTimothy Verstraeten
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2020 – today
- 2023
[c15]Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers:
A Brief Guide to Multi-Objective Reinforcement Learning and Planning. AAMAS 2023: 1988-1990- [i13]Alexandra Cimpean, Timothy Verstraeten, Lander Willem, Niel Hens, Ann Nowé, Pieter Libin:
Evaluating COVID-19 vaccine allocation policies using Bayesian m-top exploration. CoRR abs/2301.12822 (2023) - 2022
- [j3]Conor F. Hayes
, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers:
A practical guide to multi-objective reinforcement learning and planning. Auton. Agents Multi Agent Syst. 36(1): 26 (2022) - [j2]Roxana Radulescu, Timothy Verstraeten, Yijie Zhang, Patrick Mannion, Diederik M. Roijers, Ann Nowé:
Opponent learning awareness and modelling in multi-objective normal form games. Neural Comput. Appl. 34(3): 1759-1781 (2022) - [i12]Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley, Patrick Mannion:
Multi-Objective Coordination Graphs for the Expected Scalarised Returns with Generative Flow Models. CoRR abs/2207.00368 (2022) - 2021
- [j1]Pieter J. K. Libin, Lander Willem, Timothy Verstraeten, Andrea Torneri, Joris Vanderlocht, Niel Hens:
Assessing the feasibility and effectiveness of household-pooled universal testing to control COVID-19 epidemics. PLoS Comput. Biol. 17(3) (2021) - [c14]Eugenio Bargiacchi, Timothy Verstraeten, Diederik M. Roijers:
Cooperative Prioritized Sweeping. AAMAS 2021: 160-168 - [c13]Timothy Verstraeten, Pieter-Jan Daems, Eugenio Bargiacchi, Diederik M. Roijers, Pieter J. K. Libin, Jan Helsen:
Scalable Optimization for Wind Farm Control using Coordination Graphs. AAMAS 2021: 1362-1370 - [i11]Timothy Verstraeten, Pieter-Jan Daems, Eugenio Bargiacchi, Diederik M. Roijers, Pieter J. K. Libin, Jan Helsen:
Scalable Optimization for Wind Farm Control using Coordination Graphs. CoRR abs/2101.07844 (2021) - [i10]Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers:
A Practical Guide to Multi-Objective Reinforcement Learning and Planning. CoRR abs/2103.09568 (2021) - [i9]Conor F. Hayes, Timothy Verstraeten, Diederik M. Roijers, Enda Howley, Patrick Mannion:
Expected Scalarised Returns Dominance: A New Solution Concept for Multi-Objective Decision Making. CoRR abs/2106.01048 (2021) - 2020
- [c12]Timothy Verstraeten, Eugenio Bargiacchi, Pieter J. K. Libin, Diederik M. Roijers, Ann Nowé:
Thompson Sampling for Factored Multi-Agent Bandits. AAMAS 2020: 2029-2031 - [c11]Timothy Verstraeten, Pieter J. K. Libin, Ann Nowé:
Fleet Control Using Coregionalized Gaussian Process Policy Iteration. ECAI 2020: 1571-1578 - [c10]Pieter J. K. Libin, Arno Moonens, Timothy Verstraeten, Fabian Perez-Sanjines, Niel Hens, Philippe Lemey, Ann Nowé:
Deep Reinforcement Learning for Large-Scale Epidemic Control. ECML/PKDD (5) 2020: 155-170 - [i8]Eugenio Bargiacchi, Timothy Verstraeten, Diederik M. Roijers, Ann Nowé:
Model-based Multi-Agent Reinforcement Learning with Cooperative Prioritized Sweeping. CoRR abs/2001.07527 (2020) - [i7]Pieter Libin, Arno Moonens, Timothy Verstraeten, Fabian Perez-Sanjines, Niel Hens, Philippe Lemey, Ann Nowé:
Deep reinforcement learning for large-scale epidemic control. CoRR abs/2003.13676 (2020) - [i6]Roxana Radulescu, Timothy Verstraeten, Yijie Zhang, Patrick Mannion, Diederik M. Roijers, Ann Nowé:
Opponent Learning Awareness and Modelling in Multi-Objective Normal Form Games. CoRR abs/2011.07290 (2020)
2010 – 2019
- 2019
- [c9]Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys, Ann Nowé:
Thompson Sampling for m-top Exploration. BNAIC/BENELEARN 2019 - [c8]Regis Loeb, Timothy Verstraeten, Ann Nowé, Ann Dooms:
Privacy Preserving Reinforcement Learning over Distributed Datasets. BNAIC/BENELEARN 2019 - [c7]Timothy Verstraeten, Ann Nowé, Jan Helsen:
Failure Avoidance for Wind Turbines through Fleetwide Control. BNAIC/BENELEARN 2019 - [c6]Felipe Gomez Marulanda, Pieter Libin, Timothy Verstraeten, Ann Nowé:
Deep hybrid approach for 3D plane segmentation. ESANN 2019 - [c5]Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Wenjia Wang, Kristof Theys, Ann Nowé:
Bayesian Anytime m-top Exploration. ICTAI 2019: 1422-1428 - [i5]Timothy Verstraeten, Ann Nowé, Jonathan Keller, Yi Guo, Shuangwen Sheng, Jan Helsen:
Fleetwide data-enabled reliability improvement of wind turbines. CoRR abs/1903.11518 (2019) - [i4]Felipe Gomez Marulanda, Pieter Libin, Timothy Verstraeten, Ann Nowé:
IPC-Net: 3D point-cloud segmentation using deep inter-point convolutional layers. CoRR abs/1909.13726 (2019) - [i3]Timothy Verstraeten, Eugenio Bargiacchi, Pieter J. K. Libin, Diederik M. Roijers, Ann Nowé:
Thompson Sampling for Factored Multi-Agent Bandits. CoRR abs/1911.10120 (2019) - [i2]Timothy Verstraeten, Pieter J. K. Libin, Ann Nowé:
Fleet Control using Coregionalized Gaussian Process Policy Iteration. CoRR abs/1911.10121 (2019) - 2018
- [c4]Eugenio Bargiacchi, Timothy Verstraeten, Diederik M. Roijers, Ann Nowé, Hado van Hasselt:
Learning to Coordinate with Coordination Graphs in Repeated Single-Stage Multi-Agent Decision Problems. ICML 2018: 491-499 - [c3]Felipe Gomez Marulanda, Pieter Libin, Timothy Verstraeten, Ann Nowé:
IPC-Net: 3D Point-Cloud Segmentation Using Deep Inter-Point Convolutional Layers. ICTAI 2018: 293-301 - [c2]Pieter J. K. Libin, Timothy Verstraeten, Diederik M. Roijers, Jelena Grujic, Kristof Theys, Philippe Lemey, Ann Nowé:
Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies. ECML/PKDD (3) 2018: 456-471 - 2017
- [c1]Pieter Libin, Timothy Verstraeten, Kristof Theys, Diederik M. Roijers, Peter Vrancx, Ann Nowé:
Efficient Evaluation of Influenza Mitigation Strategies Using Preventive Bandits. AAMAS Workshops (Visionary Papers) 2017: 67-85 - [i1]Pieter Libin, Timothy Verstraeten, Diederik M. Roijers, Jelena Grujic, Kristof Theys, Philippe Lemey, Ann Nowé:
Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies. CoRR abs/1711.06299 (2017)
Coauthor Index
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