Print Email Facebook Twitter Improved deep reinforcement learning for robotics through distribution-based experience retention Title Improved deep reinforcement learning for robotics through distribution-based experience retention Author de Bruin, T.D. (TU Delft OLD Intelligent Control & Robotics) Kober, J. (TU Delft OLD Intelligent Control & Robotics) Tuyls, K.P. (TU Delft Delft Center for Systems and Control; University of Liverpool) Babuska, R. (TU Delft OLD Intelligent Control & Robotics) Contributor Kwon, Dong-Soo (editor) Kang, Chul-Goo (editor) Suh, Il Hong (editor) Department Delft Center for Systems and Control Date 2016 Abstract Recent years have seen a growing interest in the use of deep neural networks as function approximators in reinforcement learning. In this paper, an experience replay method is proposed that ensures that the distribution of the experiences used for training is between that of the policy and a uniform distribution. Through experiments on a magnetic manipulation task it is shown that the method reduces the need for sustained exhaustive exploration during learning. This makes it attractive in scenarios where sustained exploration is in-feasible or undesirable, such as for physical systems like robots and for life long learning. The method is also shown to improve the generalization performance of the trained policy, which can make it attractive for transfer learning. Finally, for small experience databases the method performs favorably when compared to the recently proposed alternative of using the temporal difference error to determine the experience sample distribution, which makes it an attractive option for robots with limited memory capacity. Subject DatabasesNeural networksTrainingLearning (artificial intelligence)StandardsRobot control To reference this document use: http://resolver.tudelft.nl/uuid:1f7633c7-d884-4947-8aef-0538a6cf8f74 DOI https://doi.org/10.1109/IROS.2016.7759581 Publisher IEEE, Piscataway, NJ, USA ISBN 978-1-5090-3762-9 Source Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): IROS 2016 Event 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2016, 2016-10-09 → 2016-10-14, Daejeon, Korea, Republic of Bibliographical note Accepted Author Manuscript Part of collection Institutional Repository Document type conference paper Rights © 2016 T.D. de Bruin, J. Kober, K.P. Tuyls, R. Babuska Files PDF deBruinIROS2016.pdf 3.23 MB Close viewer /islandora/object/uuid:1f7633c7-d884-4947-8aef-0538a6cf8f74/datastream/OBJ/view