| The unsurprising effectiveness of pre-trained vision models for control S Parisi, A Rajeswaran, S Purushwalkam, A Gupta International Conference on Machine Learning, 17359-17371, 2022 | 185 | 2022 |
| Policy gradient approaches for multi-objective sequential decision making S Parisi, M Pirotta, N Smacchia, L Bascetta, M Restelli 2014 International Joint Conference on Neural Networks (IJCNN), 2323-2330, 2014 | 84 | 2014 |
| Multi-objective reinforcement learning with continuous pareto frontier approximation M Pirotta, S Parisi, M Restelli Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015 | 81 | 2015 |
| Multi-objective Reinforcement Learning through Continuous Pareto Manifold Approximation S Parisi, M Pirotta, M Restelli Journal of Artificial Intelligence Research 57, 187-227, 2016 | 64 | 2016 |
| Manifold-based multi-objective policy search with sample reuse S Parisi, M Pirotta, J Peters Neurocomputing, Special Issue on Multi-objective Reinforcement Learning 263 …, 2017 | 57 | 2017 |
| Interesting object, curious agent: Learning task-agnostic exploration S Parisi, V Dean, D Pathak, A Gupta Advances in Neural Information Processing Systems 34, 20516-20530, 2021 | 55 | 2021 |
| TD-regularized actor-critic methods S Parisi, V Tangkaratt, J Peters, ME Khan Machine Learning 108, 1467-1501, 2019 | 48 | 2019 |
| Reinforcement learning algorithms: analysis and applications B Belousov, H Abdulsamad, P Klink, S Parisi, J Peters Springer, 2021 | 27 | 2021 |
| Goal-Driven Dimensionality Reduction for Reinforcement Learning S Parisi, S Ramstedt, J Peters 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017 | 22 | 2017 |
| Policy search with high-dimensional context variables V Tangkaratt, H van Hoof, S Parisi, G Neumann, J Peters, M Sugiyama Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 22 | 2017 |
| Reinforcement learning vs human programming in tetherball robot games S Parisi, H Abdulsamad, A Paraschos, C Daniel, J Peters 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015 | 20 | 2015 |
| 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), 2022 | 11* | 2022 |
| Policy gradient approaches for multi-objective sequential decision making: A comparison S Parisi, M Pirotta, N Smacchia, L Bascetta, M Restelli 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2014 | 11 | 2014 |
| Local-utopia Policy Selection for Multi-objective Reinforcement Learning S Parisi, A Blank, T Viernickel, J Peters 2016 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2016 | 3 | 2016 |
| Reinforcement Learning with Sparse and Multiple Rewards S Parisi Technische Universität Darmstadt, 2020 | 2 | 2020 |
| Monitored Markov Decision Processes S Parisi, M Mohammedalamen, A Kazemipour, ME Taylor, M Bowling arXiv preprint arXiv:2402.06819, 2024 | 1 | 2024 |
| Beyond Optimism: Exploration With Partially Observable Rewards S Parisi, A Kazemipour, M Bowling arXiv preprint arXiv:2406.13909, 2024 | | 2024 |
| Policy search with high-dimensional context variables H van Hoof, J Peters, M Sugiyama, S Parisi, V Tangkaratt, G Neumann University of Lincoln, 2017 | | 2017 |
| Studio e analisi di algoritmi di apprendimento per rinforzo policy gradient per la risoluzione di problemi decisionali multiobiettivo S PARISI, N SMACCHIA Politecnico di Milano, 2012 | | 2012 |