Sharing knowledge in multi-task deep reinforcement learning C D'Eramo, D Tateo, A Bonarini, M Restelli, J Peters 8th International Conference on Learning Representations, (ICLR) 2020, Addis …, 2020 | 120* | 2020 |
Mushroomrl: Simplifying reinforcement learning research C D'Eramo, D Tateo, A Bonarini, M Restelli, J Peters Journal of Machine Learning Research 22 (131), 1-5, 2021 | 65 | 2021 |
ImitationFlow: Learning Deep Stable Stochastic Dynamic Systems by Normalizing Flows J Urain, M Ginesi, D Tateo, J Peters 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020 | 42 | 2020 |
Robot reinforcement learning on the constraint manifold P Liu, D Tateo, HB Ammar, J Peters Conference on Robot Learning, 1357-1366, 2022 | 37 | 2022 |
Multiagent Connected Path Planning: PSPACE-Completeness and How to Deal with It D Tateo, J Banfi, A Riva, F Amigoni, A Bonarini Thirty-Second AAAI Conference on Artificial Intelligence (AAAI2018), 4735-4742, 2018 | 24 | 2018 |
Learning-based design and control for quadrupedal robots with parallel-elastic actuators F Bjelonic, J Lee, P Arm, D Sako, D Tateo, J Peters, M Hutter IEEE Robotics and Automation Letters 8 (3), 1611-1618, 2023 | 22 | 2023 |
Regularized deep signed distance fields for reactive motion generation P Liu, K Zhang, D Tateo, S Jauhri, J Peters, G Chalvatzaki 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2022 | 21 | 2022 |
Continuous action reinforcement learning from a mixture of interpretable experts R Akrour, D Tateo, J Peters IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (10), 6795 …, 2021 | 20* | 2021 |
LS-IQ: Implicit reward regularization for inverse reinforcement learning F Al-Hafez, D Tateo, O Arenz, G Zhao, J Peters arXiv preprint arXiv:2303.00599, 2023 | 16 | 2023 |
Gradient-based minimization for multi-expert inverse reinforcement learning D Tateo, M Pirotta, M Restelli, A Bonarini 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2017 | 14 | 2017 |
Learning stable vector fields on lie groups J Urain, D Tateo, J Peters IEEE Robotics and Automation Letters 7 (4), 12569-12576, 2022 | 11 | 2022 |
Long-term visitation value for deep exploration in sparse-reward reinforcement learning S Parisi, D Tateo, M Hensel, C D’eramo, J Peters, J Pajarinen Algorithms 15 (3), 81, 2022 | 8 | 2022 |
Efficient and reactive planning for high speed robot air hockey P Liu, D Tateo, H Bou-Ammar, J Peters 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2021 | 8 | 2021 |
Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks P Kicki, P Liu, D Tateo, H Bou-Ammar, K Walas, P Skrzypczyński, J Peters IEEE Transactions on Robotics 40, 277 - 297, 2023 | 7 | 2023 |
Safe reinforcement learning of dynamic high-dimensional robotic tasks: navigation, manipulation, interaction P Liu, K Zhang, D Tateo, S Jauhri, Z Hu, J Peters, G Chalvatzaki 2023 IEEE International Conference on Robotics and Automation (ICRA), 9449-9456, 2023 | 7 | 2023 |
An empirical analysis of measure-valued derivatives for policy gradients J Carvalho, D Tateo, F Muratore, J Peters 2021 International Joint Conference on Neural Networks (IJCNN), 1-10, 2021 | 6 | 2021 |
Dimensionality reduction and prioritized exploration for policy search M Memmel, P Liu, D Tateo, J Peters International Conference on Artificial Intelligence and Statistics, 2134-2157, 2022 | 5 | 2022 |
Towards Reinforcement Learning of Human Readable Policies R Akrour, D Tateo, J Peters ECML/PKDD Workshop on Deep Continuous-Discrete Machine Learning, 2019 | 5 | 2019 |
LocoMuJoCo: A Comprehensive Imitation Learning Benchmark for Locomotion F Al-Hafez, G Zhao, J Peters, D Tateo arXiv preprint arXiv:2311.02496, 2023 | 4 | 2023 |
Graph-Based Design of Hierarchical Reinforcement Learning Agents D Tateo, IS Erdenlig, A Bonarini IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019 | 2 | 2019 |