Raphael Fonteneau
Raphael Fonteneau
Researcher @ University of Liège, Liège, Belgium
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
Reinforcement learning for electric power system decision and control: Past considerations and perspectives
M Glavic, R Fonteneau, D Ernst
IFAC-PapersOnLine 50 (1), 6918-6927, 2017
Deep reinforcement learning solutions for energy microgrids management
V François-Lavet, D Taralla, D Ernst, R Fonteneau
European Workshop on Reinforcement Learning (EWRL 2016), 2016
How to discount deep reinforcement learning: Towards new dynamic strategies
V François-Lavet, R Fonteneau, D Ernst
arXiv preprint arXiv:1512.02011, 2015
Batch mode reinforcement learning based on the synthesis of artificial trajectories
R Fonteneau, SA Murphy, L Wehenkel, D Ernst
Annals of Operations Research 208 (1), 383-416, 2013
Phase identification of smart meters by clustering voltage measurements
F Olivier, A Sutera, P Geurts, R Fonteneau, D Ernst
2018 Power Systems Computation Conference (PSCC), 1-8, 2018
The role of power-to-gas and carbon capture technologies in cross-sector decarbonisation strategies
M Berger, D Radu, R Fonteneau, T Deschuyteneer, G Detienne, D Ernst
Electric Power Systems Research 180, 106039, 2020
Learning exploration/exploitation strategies for single trajectory reinforcement learning
M Castronovo, F Maes, R Fonteneau, D Ernst
European Workshop on Reinforcement Learning (EWRL 2012), 2012
Artificial intelligence in video games: Towards a unified framework
F Safadi, R Fonteneau, D Ernst
International Journal of Computer Games Technology 2015 (1), 271296, 2015
Mathematical modeling of HIV dynamics after antiretroviral therapy initiation: a review
PS Rivadeneira, CH Moog, GB Stan, C Brunet, F Raffi, V Ferré, ...
BioResearch open access 3 (5), 233-241, 2014
Policy search in a space of simple closed-form formulas: Towards interpretability of reinforcement learning
F Maes, R Fonteneau, L Wehenkel, D Ernst
Discovery Science: 15th International Conference, DS 2012, Lyon, France …, 2012
On overfitting and asymptotic bias in batch reinforcement learning with partial observability
V François-Lavet, G Rabusseau, J Pineau, D Ernst, R Fonteneau
Journal of Artificial Intelligence Research 65, 1-30, 2019
Model-free Monte Carlo-like policy evaluation
R Fonteneau, S Murphy, L Wehenkel, D Ernst
Thirteenth International Conference on Artificial Intelligence and …, 2010
Critical time windows for renewable resource complementarity assessment
M Berger, D Radu, R Fonteneau, R Henry, M Glavic, X Fettweis, M Le Du, ...
Energy 198, 117308, 2020
Complementarity assessment of south Greenland katabatic flows and West Europe wind regimes
D Radu, M Berger, R Fonteneau, S Hardy, X Fettweis, M Le Du, ...
Energy 175, 393-401, 2019
Foreseeing new control challenges in electricity prosumer communities
F Olivier, D Marulli, D Ernst, R Fonteneau
The 10th Bulk Power Systems Dynamics and Control Symposium–IREP’2017, 2017
Optimistic planning for belief-augmented Markov decision processes
R Fonteneau, L Busoniu, R Munos
IEEE International Symposium on Adaptive Dynamic Programming and …, 2013
Imitative learning for real-time strategy games
Q Gemine, F Safadi, R Fonteneau, D Ernst
IEEE Conference of Computational Intelligence and Games, 2012
Network tariffs and the integration of prosumers: The case of Wallonia
MM de Villena, J Jacqmin, R Fonteneau, A Gautier, D Ernst
Energy Policy 150, 112065, 2021
Towards the minimization of the levelized energy costs of microgrids using both long-term and short-term storage devices
V François-Lavet, Q Gemine, D Ernst, R Fonteneau
9781498719704, 2016
Inferring bounds on the performance of a control policy from a sample of trajectories
R Fonteneau, S Murphy, L Wehenkel, D Ernst
2009 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2009
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