Continuous control with deep reinforcement learning TP Lillicrap arXiv preprint arXiv:1509.02971, 2015 | 17123 | 2015 |
Mujoco: A physics engine for model-based control E Todorov, T Erez, Y Tassa 2012 IEEE/RSJ international conference on intelligent robots and systems …, 2012 | 6069 | 2012 |
Emergence of locomotion behaviours in rich environments N Heess, D Tb, S Sriram, J Lemmon, J Merel, G Wayne, Y Tassa, T Erez, ... arXiv preprint arXiv:1707.02286, 2017 | 1127 | 2017 |
Synthesis and stabilization of complex behaviors through online trajectory optimization Y Tassa, T Erez, E Todorov 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2012 | 999 | 2012 |
Learning continuous control policies by stochastic value gradients N Heess, G Wayne, D Silver, T Lillicrap, T Erez, Y Tassa Advances in neural information processing systems 28, 2015 | 677 | 2015 |
Deepmind control suite Y Tassa, Y Doron, A Muldal, T Erez, Y Li, DL Casas, D Budden, ... arXiv preprint arXiv:1801.00690, 2018 | 621 | 2018 |
Continuous control with deep reinforcement learning. arXiv 2015 TP Lillicrap, JJ Hunt, A Pritzel, N Heess, T Erez, Y Tassa, D Silver, ... arXiv preprint arXiv:1509.02971, 1935 | 574 | 1935 |
Diego de Las Casas, David Budden, Abbas Abdolmaleki, Josh Merel, Andrew Lefrancq, et al. Deepmind control suite Y Tassa, Y Doron, A Muldal, T Erez, Y Li arXiv preprint arXiv:1801.00690 2 (6), 7, 2018 | 531* | 2018 |
Simulation tools for model-based robotics: Comparison of bullet, havok, mujoco, ode and physx T Erez, Y Tassa, E Todorov 2015 IEEE international conference on robotics and automation (ICRA), 4397-4404, 2015 | 410 | 2015 |
Reinforcement and imitation learning for diverse visuomotor skills Y Zhu, Z Wang, J Merel, A Rusu, T Erez, S Cabi, S Tunyasuvunakool, ... arXiv preprint arXiv:1802.09564, 2018 | 370 | 2018 |
dm_control: Software and tasks for continuous control S Tunyasuvunakool, A Muldal, Y Doron, S Liu, S Bohez, J Merel, T Erez, ... Software Impacts 6, 100022, 2020 | 360 | 2020 |
Data-efficient deep reinforcement learning for dexterous manipulation I Popov, N Heess, T Lillicrap, R Hafner, G Barth-Maron, M Vecerik, ... arXiv preprint arXiv:1704.03073, 2017 | 317 | 2017 |
Language to rewards for robotic skill synthesis W Yu, N Gileadi, C Fu, S Kirmani, KH Lee, MG Arenas, HTL Chiang, ... arXiv preprint arXiv:2306.08647, 2023 | 187 | 2023 |
An integrated system for real-time model predictive control of humanoid robots T Erez, K Lowrey, Y Tassa, V Kumar, S Kolev, E Todorov 2013 13th IEEE-RAS International conference on humanoid robots (Humanoids …, 2013 | 183 | 2013 |
Receding horizon differential dynamic programming Y Tassa, T Erez, W Smart Advances in neural information processing systems 20, 2007 | 168 | 2007 |
Continuous control with deep reinforcement learning Y Bengio, TP Lillicrap, JJ Hunt, A Pritzel, N Heess, T Erez, D Wierstra Found. TrendsŪ Mach. Learn 2, 1-127, 2009 | 163 | 2009 |
Catch & carry: reusable neural controllers for vision-guided whole-body tasks J Merel, S Tunyasuvunakool, A Ahuja, Y Tassa, L Hasenclever, V Pham, ... ACM Transactions on Graphics (TOG) 39 (4), 39: 1-39: 12, 2020 | 122 | 2020 |
Infinite-Horizon Model Predictive Control for Periodic Tasks with Contacts T Erez, Y Tassa, E Todorov Robotics: Science and Systems, 2011 | 108 | 2011 |
Infinite-Horizon Model Predictive Control for Periodic Tasks with Contacts T Erez, Y Tassa, E Todorov Robotics: Science and Systems, 2011 | 108 | 2011 |
& Wierstra, D.(2015). Continuous control with deep reinforcement learning TP Lillicrap, JJ Hunt, A Pritzel, N Heess, T Erez, Y Tassa arXiv preprint arXiv:1509.02971, 0 | 100 | |