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2020 – today
- 2024
[j6]Gaspard Lambrechts, Adrien Bolland, Damien Ernst:
Informed POMDP: Leveraging Additional Information in Model-Based RL. RLJ 2: 763-784 (2024)- [i10]Samy Aittahar, Adrien Bolland, Guillaume Derval, Damien Ernst:
Optimal Control of Renewable Energy Communities subject to Network Peak Fees with Model Predictive Control and Reinforcement Learning Algorithms. CoRR abs/2401.16321 (2024) - [i9]Adrien Bolland, Gaspard Lambrechts, Damien Ernst:
Behind the Myth of Exploration in Policy Gradients. CoRR abs/2402.00162 (2024) - [i8]Marine Cauz, Adrien Bolland, Nicolas Wyrsch, Christophe Ballif:
Reinforcement Learning for Efficient Design and Control Co-optimisation of Energy Systems. CoRR abs/2406.19825 (2024) - [i7]Matthias Pirlet, Adrien Bolland, Gilles Louppe, Damien Ernst:
Costs Estimation in Unit Commitment Problems using Simulation-Based Inference. CoRR abs/2409.03588 (2024) - 2023
- [j5]Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, Damien Ernst:
Distributional reinforcement learning with unconstrained monotonic neural networks. Neurocomputing 534: 199-219 (2023) - [j4]Adrien Bolland, Gilles Louppe, Damien Ernst:
Policy Gradient Algorithms Implicitly Optimize by Continuation. Trans. Mach. Learn. Res. 2023 (2023) - [i6]Adrien Bolland, Gilles Louppe, Damien Ernst:
Policy Gradient Algorithms Implicitly Optimize by Continuation. CoRR abs/2305.06851 (2023) - [i5]Gaspard Lambrechts, Adrien Bolland, Damien Ernst:
Informed POMDP: Leveraging Additional Information in Model-Based RL. CoRR abs/2306.11488 (2023) - 2022
- [j3]Adrien Bolland, Ioannis Boukas, Mathias Berger
, Damien Ernst:
Jointly Learning Environments and Control Policies with Projected Stochastic Gradient Ascent. J. Artif. Intell. Res. 73: 117-171 (2022) - [j2]Gaspard Lambrechts, Adrien Bolland, Damien Ernst:
Recurrent networks, hidden states and beliefs in partially observable environments. Trans. Mach. Learn. Res. 2022 (2022) - [i4]Gaspard Lambrechts, Adrien Bolland, Damien Ernst:
Recurrent networks, hidden states and beliefs in partially observable environments. CoRR abs/2208.03520 (2022) - 2021
- [j1]Ioannis Boukas, Damien Ernst, Thibaut Théate, Adrien Bolland, Alexandre Huynen, Martin Buchwald, Christelle Wynants, Bertrand Cornélusse:
A deep reinforcement learning framework for continuous intraday market bidding. Mach. Learn. 110(9): 2335-2387 (2021) - [i3]Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, Damien Ernst:
Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks. CoRR abs/2106.03228 (2021) - 2020
- [i2]Ioannis Boukas, Damien Ernst, Thibaut Théate, Adrien Bolland, Alexandre Huynen, Martin Buchwald, Christelle Wynants, Bertrand Cornélusse:
A Deep Reinforcement Learning Framework for Continuous Intraday Market Bidding. CoRR abs/2004.05940 (2020) - [i1]Adrien Bolland, Ioannis Boukas, François Cornet, Mathias Berger, Damien Ernst:
Learning optimal environments using projected stochastic gradient ascent. CoRR abs/2006.01738 (2020)
Coauthor Index
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