About Me
I am a PhD student in artificial intelligence at the university of Liège doing researches in deep RL with applications to the renewable energy transition. Beyond artificial intelligence, I am also interested in languages, culture, music and sport. I love classical music and good old rock. In my free time, I relax through sport and walks in the nature.
Recent Work
Policy Gradient Algorithms Implicitly Optimize by Continuation
Adrien Bolland, Gilles Louppe, Damien Ernst
Transactions on Machine Learning Research, 2023
Informed POMDP : Leveraging Additional Information in Model-Based RL
Gaspard Lambrechts, Adrien Bolland, Damien Ernst
ICML Workshop on New Frontiers in Learning, Control, and Dynamical Systems, 2023
Reinforcement Learning for Joint Design and Control of Battery-PV Systems
Marine Cauz, Adrien Bolland, Bardhyl Miftari, Lionel Perret, Christophe Ballif, Nicolas Wyrsch
Proceedings of ECOS 2023 : The 36th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems, 2023
Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks
Thibaut Théate, Antoine Wehenkel, Adrien Bolland, Gilles Louppe, Damien Ernst
Neurocomputing, 2023
Recurrent networks, hidden states and beliefs in partially observable environments
Gaspard Lambrechts, Adrien Bolland, Damien Ernst
Transactions on Machine Learning Research, 2022
Jointly Learning Environments and Control Policies with Projected Stochastic Gradient Ascent
Adrien Bolland, Ioannis Boukas, Mathias Berger, Damien Ernst
Journal of Artificial Intelligence Research, 2022
Graph-Based Optimization Modeling Language: A Tutorial
Mathias Berger, Adrien Bolland, Bardhyl Miftari, Hatim Djelassi, Damien Ernst
preprint, 2021
A deep reinforcement learning framework for continuous intraday market bidding
Ioannis Boukas, Damien Ernst, Thibaut Théate, Adrien Bolland, Alexandre Huynen, Martin Buchwald, Christelle Wynants, Bertrand Cornélusse
Machine Learning, 2021