| Markov decision processes F Garcia, E Rachelson Markov Decision Processes in Artificial Intelligence, 1-38, 2013 | 104 | 2013 |
| Non-Stationary Markov Decision Processes, a Worst-Case Approach using Model-Based Reinforcement Learning E Lecarpentier, E Rachelson Advances in Neural Information Processing Systems 32, 7216-7225, 2019 | 82 | 2019 |
| Formal detection of attentional tunneling in human operator–automation interactions N Régis, F Dehais, E Rachelson, C Thooris, S Pizziol, M Causse, ... IEEE Transactions on Human-Machine Systems 44 (3), 326-336, 2014 | 70 | 2014 |
| The aircraft runway scheduling problem: A survey S Ikli, C Mancel, M Mongeau, X Olive, E Rachelson Computers & Operations Research 132, 105336, 2021 | 47 | 2021 |
| On the locality of action domination in sequential decision making E Rachelson, MG Lagoudakis 11th International Symposium on Artificial Intelligence and Mathematics, 2010 | 43 | 2010 |
| Lipschitz lifelong reinforcement learning E Lecarpentier, D Abel, K Asadi, Y Jinnai, E Rachelson, ML Littman Proceedings of the AAAI Conference on Artificial Intelligence 35 (9), 8270-8278, 2020 | 36 | 2020 |
| A simulation-based approach for solving generalized semi-markov decision processes E Rachelson, G Quesnel, F Garcia, P Fabiani ECAI 2008, 583-587, 2008 | 36* | 2008 |
| Learning to handle parameter perturbations in combinatorial optimization: an application to facility location A Lodi, L Mossina, E Rachelson EURO Journal on Transportation and Logistics 9 (4), 100023, 2020 | 30 | 2020 |
| Look where you look! saliency-guided q-networks for generalization in visual reinforcement learning D Bertoin, A Zouitine, M Zouitine, E Rachelson Advances in Neural Information Processing Systems 35, 30693-30706, 2022 | 19* | 2022 |
| Large batch experience replay T Lahire, M Geist, E Rachelson International Conference on Machine Learning, 2022 | 16 | 2022 |
| Open Loop Execution of Tree-Search Algorithms E Lecarpentier, G Infantes, C Lesire, E Rachelson Twenty-Seventh International Joint Conference on Artificial Intelligence …, 2018 | 16* | 2018 |
| Timdppoly: An improved method for solving time-dependent mdps E Rachelson, P Fabiani, F Garcia 2009 21st IEEE International Conference on Tools with Artificial …, 2009 | 16 | 2009 |
| Extending the Bellman equation for MDPs to continuous actions and continuous time in the discounted case E Rachelson, F Garcia, P Fabiani International Symposium on Artificial Intelligence and Mathematics, 2008 | 16 | 2008 |
| Optimal sample selection for batch-mode reinforcement learning E Rachelson, F Schnitzler, L Wehenkel, D Ernst 3rd International Conference on Agents and Artificial Intelligence, 2011 | 15 | 2011 |
| Local feature swapping for generalization in reinforcement learning D Bertoin, E Rachelson International Conference on Learning Representations, 2022 | 14 | 2022 |
| Combining mixed integer programming and supervised learning for fast re-planning E Rachelson, AB Abbes, S Diemer 2010 22nd IEEE International Conference on Tools with Artificial …, 2010 | 14 | 2010 |
| An optimistic planning approach for the aircraft landing problem S Ikli, C Mancel, M Mongeau, X Olive, E Rachelson Air Traffic Management and Systems IV: Selected Papers of the 6th ENRI …, 2021 | 9 | 2021 |
| Coupling Mathematical Optimization and Machine Learning for the Aircraft Landing Problem S Ikli, C Mancel, M Mongeau, X Olive, E Rachelson ICRAT 2020, 9th International Conference for Research in Air Transportation, 2020 | 9 | 2020 |
| Approximate inference in related multi-output Gaussian process regression A Chiplunkar, E Rachelson, M Colombo, J Morlier Pattern Recognition Applications and Methods: 5th International Conference …, 2017 | 8 | 2017 |
| Une approche du traitement du temps dans le cadre MDP: trois méthodes de découpage de la droite temporelle E Rachelson, P Fabiani, JL Farges, F Teichteil-Königsbuch, F Garcia | 8 | 2006 |
Frédérick GarciaINRA Research Director (DR1), MIAT (INRA), TMBI (Univ. Toulouse)toulouse.inra.fr의 이메일 확인됨
