| A survey of preference-based reinforcement learning methods C Wirth, R Akrour, G Neumann, J Fürnkranz Journal of Machine Learning Research 18 (136), 1-46, 2017 | 156 | 2017 |
| April: Active preference learning-based reinforcement learning R Akrour, M Schoenauer, M Sebag Joint European conference on machine learning and knowledge discovery in …, 2012 | 122 | 2012 |
| Preference-based policy learning R Akrour, M Schoenauer, M Sebag Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011 | 111 | 2011 |
| Programming by feedback R Akrour, M Schoenauer, M Sebag, JC Souplet International Conference on Machine Learning, 1503-1511, 2014 | 53 | 2014 |
| Model-free trajectory optimization for reinforcement learning R Akrour, G Neumann, H Abdulsamad, A Abdolmaleki International Conference on Machine Learning, 2961-2970, 2016 | 42 | 2016 |
| 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 | 19 | 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 | 19 | 2018 |
| Compatible natural gradient policy search J Pajarinen, HL Thai, R Akrour, J Peters, G Neumann Machine Learning 108 (8), 1443-1466, 2019 | 17 | 2019 |
| Local Bayesian optimization of motor skills R Akrour, D Sorokin, J Peters, G Neumann International Conference on Machine Learning, 41-50, 2017 | 17 | 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 | 15 | 2018 |
| Interactive robot education R Akrour, M Schoenauer, M Sebag ECML/PKDD Workshop on Reinforcement Learning with Generalized Feedback …, 2013 | 15 | 2013 |
| 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 | 10 | 2017 |
| Projections for approximate policy iteration algorithms R Akrour, J Pajarinen, J Peters, G Neumann International Conference on Machine Learning, 181-190, 2019 | 6 | 2019 |
| Hierarchical tactile-based control decomposition of dexterous in-hand manipulation tasks F Veiga, R Akrour, J Peters Frontiers in Robotics and AI 7, 521448, 2020 | 5 | 2020 |
| Preference-based reinforcement learning R Akrour, M Schoenauer, M Sebag Choice Models and Preference Learning Workshop at NIPS 11, 2011 | 5 | 2011 |
| An upper bound of the bias of nadaraya-watson kernel regression under lipschitz assumptions S Tosatto, R Akrour, J Peters Stats 4 (1), 1-17, 2021 | 3 | 2021 |
| Reinforcement learning from a mixture of interpretable experts R Akrour, D Tateo, J Peters | 3 | 2020 |
| Empowered skills A Gabriel, R Akrour, J Peters, G Neumann 2017 IEEE International Conference on Robotics and Automation (ICRA), 6435-6441, 2017 | 3 | 2017 |
| 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 | 2 | 2019 |
| Towards Reinforcement Learning of Human Readable Policies R Akrour, D Tateo, J Peters Workshop on Deep Continuous-Discrete Machine Learning, 2019 | 2 | 2019 |
