| April: Active preference learning-based reinforcement learning R Akrour, M Schoenauer, M Sebag Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012 | 91 | 2012 |
| Preference-based policy learning R Akrour, M Schoenauer, M Sebag Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011 | 88 | 2011 |
| A survey of preference-based reinforcement learning methods C Wirth, R Akrour, G Neumann, J Fürnkranz The Journal of Machine Learning Research 18 (1), 4945-4990, 2017 | 84 | 2017 |
| Programming by feedback R Akrour, M Schoenauer, M Sebag, JC Souplet International Conference on Machine Learning 32, 1503-1511, 2014 | 44 | 2014 |
| Model-free trajectory optimization for reinforcement learning R Akrour, G Neumann, H Abdulsamad, A Abdolmaleki International Conference on Machine Learning, 2961-2970, 2016 | 32 | 2016 |
| Interactive robot education R Akrour, M Schoenauer, M Sebag | 15 | 2013 |
| Sample and feedback efficient hierarchical reinforcement learning from human preferences R Pinsler, R Akrour, T Osa, J Peters, G Neumann 2018 IEEE International Conference on Robotics and Automation (ICRA), 596-601, 2018 | 14 | 2018 |
| Model-free trajectory-based policy optimization with monotonic improvement R Akrour, A Abdolmaleki, H Abdulsamad, J Peters, G Neumann The Journal of Machine Learning Research 19 (1), 565-589, 2018 | 11 | 2018 |
| Local Bayesian optimization of motor skills R Akrour, D Sorokin, J Peters, G Neumann | 11 | 2017 |
| Regularizing reinforcement learning with state abstraction R Akrour, F Veiga, J Peters, G Neumann 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 9 | 2018 |
| Compatible natural gradient policy search J Pajarinen, HL Thai, R Akrour, J Peters, G Neumann Machine Learning 108 (8-9), 1443-1466, 2019 | 7 | 2019 |
| Layered direct policy search for learning hierarchical skills F End, R Akrour, J Peters, G Neumann 2017 IEEE International Conference on Robotics and Automation (ICRA), 6442-6448, 2017 | 5 | 2017 |
| Empowered skills A Gabriel, R Akrour, J Peters, G Neumann 2017 IEEE International Conference on Robotics and Automation (ICRA), 6435-6441, 2017 | 5 | 2017 |
| Projections for approximate policy iteration algorithms R Akrour, J Pajarinen, J Peters, G Neumann International Conference on Machine Learning, 181-190, 2019 | 4 | 2019 |
| „Preference-based Reinforcement Learning “ R Akrour, M Schoenauer, M Sebag Choice Models and Preference Learning Workshop at NIPS 11, 2011 | 4 | 2011 |
| Direct value learning: a rank-invariant approach to reinforcement learning B Mayeur, R Akrour, M Sebag | 2 | 2014 |
| Direct value learning: A preference-based approach to reinforcement learning D Meunier, Y Deguchi, R Akrour, E Suzuki, M Schoenauer, M Sebag | 2 | 2012 |
| An Upper Bound of the Bias of Nadaraya-Watson Kernel Regression under Lipschitz Assumptions S Tosatto, R Akrour, J Peters arXiv preprint arXiv:2001.10972, 2020 | 1 | 2020 |
| Learning Replanning Policies With Direct Policy Search F Brandherm, J Peters, G Neumann, R Akrour IEEE Robotics and Automation Letters 4 (2), 2196-2203, 2019 | 1 | 2019 |
| Anti imitation-based policy learning M Sebag, R Akrour, B Mayeur, M Schoenauer Joint European Conference on Machine Learning and Knowledge Discovery in …, 2016 | 1 | 2016 |
