Sharing Knowledge in Multi-Task Deep Reinforcement Learning C D'Eramo, D Tateo, A Bonarini, M Restelli, J Peters International Conference on Learning Representations (ICLR), 2020 | 122* | 2020 |
Mushroomrl: Simplifying reinforcement learning research C D'Eramo, D Tateo, A Bonarini, M Restelli, J Peters Journal of Machine Learning Research (JMLR) 22, 1-5, 2020 | 72 | 2020 |
Estimating the Maximum Expected Value through Gaussian Approximation C D’Eramo, A Nuara, M Restelli International Conference on Machine Learning (ICML), 1032-1040, 2016 | 55 | 2016 |
Self-Paced Deep Reinforcement Learning P Klink, C D'Eramo, J Peters, J Pajarinen Advances in Neural Information Processing Systems (NeurIPS), 2020 | 50 | 2020 |
Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning AS Morgan, D Nandha, G Chalvatzaki, C D'Eramo, AM Dollar, J Peters International Conference on Robotics and Automation (ICRA), 2021 | 48* | 2021 |
Boosted Fitted Q-Iteration S Tosatto, M Pirotta, C D'Eramo, M Restelli International Conference on Machine Learning (ICML), 3434-3443, 2017 | 47 | 2017 |
Curriculum reinforcement learning via constrained optimal transport P Klink, H Yang, C D’Eramo, J Peters, J Pajarinen International Conference on Machine Learning (ICML), 11341-11358, 2022 | 33 | 2022 |
Composable energy policies for reactive motion generation and reinforcement learning J Urain, A Li, P Liu, C D’Eramo, J Peters The International Journal of Robotics Research (IJRR), 2023 | 25 | 2023 |
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning P Klink, H Abdulsamad, B Belousov, C D'Eramo, J Peters, J Pajarinen Journal of Machine Learning Research (JMLR) 22, 1-52, 2021 | 24 | 2021 |
Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems C D'Eramo, A Nuara, M Pirotta, R Marcello AAAI Conference on Artificial Intelligence, 1840-1846, 2017 | 24 | 2017 |
Multi-channel interactive reinforcement learning for sequential tasks D Koert, M Kircher, V Salikutluk, C D'Eramo, J Peters Frontiers in Robotics and AI 7, 97, 2020 | 16 | 2020 |
Deep reinforcement learning with weighted Q-Learning A Cini, C D'Eramo, J Peters, C Alippi arXiv preprint arXiv:2003.09280, 2020 | 14 | 2020 |
Exploiting Action-Value Uncertainty to Drive Exploration in Reinforcement Learning C D’Eramo, A Cini, M Restelli 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 14 | 2019 |
Convex regularization in Monte-Carlo tree search TQ Dam, C D’Eramo, J Peters, J Pajarinen International Conference on Machine Learning (ICML), 2365-2375, 2021 | 10 | 2021 |
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 | 9 | 2022 |
Generalized Mean Estimation in Monte-Carlo Tree Search T Dam, P Klink, C D'Eramo, J Peters, J Pajarinen International Joint Conference on Artificial Intelligence (IJCAI), 2020 | 9 | 2020 |
Boosted Curriculum Reinforcement Learning P Klink, C D'Eramo, J Peters, J Pajarinen International Conference on Learning Representations (ICLR), 2022 | 8 | 2022 |
Gaussian approximation for bias reduction in Q-learning C D'Eramo, A Cini, A Nuara, M Pirotta, C Alippi, J Peters, M Restelli Journal of Machine Learning Research (JMLR) 22, 1-51, 2021 | 6 | 2021 |
Multi-Task Reinforcement Learning with Mixture of Orthogonal Experts A Hendawy, J Peters, C D'Eramo International Conference on Learning Representations (ICLR), 2024 | 5 | 2024 |
Prioritized sampling with intrinsic motivation in multi-task reinforcement learning C D'Eramo, G Chalvatzaki 2022 International Joint Conference on Neural Networks (IJCNN), 1-8, 2022 | 5 | 2022 |