暂无分享,去创建一个
Yuval Tassa | Nicolas Heess | Tom Erez | Leonard Hasenclever | Arun Ahuja | Greg Wayne | Saran Tunyasuvunakool | Josh Merel | Vu Pham | N. Heess | Greg Wayne | T. Erez | Yuval Tassa | J. Merel | Arun Ahuja | Vu Pham | S. Tunyasuvunakool | Leonard Hasenclever | Tom Erez
[1] Yuval Tassa,et al. MuJoCo: A physics engine for model-based control , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[2] Stefan Schaal,et al. Computational approaches to motor learning by imitation. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[3] Joonho Lee,et al. Learning agile and dynamic motor skills for legged robots , 2019, Science Robotics.
[4] Jonathan W. Hurst,et al. Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie , 2019, ArXiv.
[5] Sergey Levine,et al. Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).
[6] Zoran Popovic,et al. Discovery of complex behaviors through contact-invariant optimization , 2012, ACM Trans. Graph..
[7] Javier R. Movellan,et al. STAC: Simultaneous tracking and calibration , 2013, 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids).
[8] Peter Englert,et al. Learning manipulation skills from a single demonstration , 2018, Int. J. Robotics Res..
[9] Sergey Levine,et al. Learning Latent Plans from Play , 2019, CoRL.
[10] Wojciech Zaremba,et al. Domain randomization for transferring deep neural networks from simulation to the real world , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[11] Aude Billard,et al. Catching Objects in Flight , 2014, IEEE Transactions on Robotics.
[12] Atil Iscen,et al. Sim-to-Real: Learning Agile Locomotion For Quadruped Robots , 2018, Robotics: Science and Systems.
[13] Xinyu Liu,et al. Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics , 2017, Robotics: Science and Systems.
[14] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[15] Jan Peters,et al. Noname manuscript No. (will be inserted by the editor) Policy Search for Motor Primitives in Robotics , 2022 .
[16] Scott Niekum,et al. Learning and generalization of complex tasks from unstructured demonstrations , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[17] Yuval Tassa,et al. Learning human behaviors from motion capture by adversarial imitation , 2017, ArXiv.
[18] Sergey Levine,et al. Learning Dexterous Manipulation Policies from Experience and Imitation , 2016, ArXiv.
[19] H. Francis Song,et al. V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control , 2019, ICLR.
[20] Razvan Pascanu,et al. Sim-to-Real Robot Learning from Pixels with Progressive Nets , 2016, CoRL.
[21] Stefan Schaal,et al. Robot Learning From Demonstration , 1997, ICML.
[22] Demis Hassabis,et al. A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play , 2018, Science.
[23] Joonho Lee,et al. Robust Recovery Controller for a Quadrupedal Robot using Deep Reinforcement Learning , 2019, ArXiv.
[24] Oussama Khatib,et al. Synthesis of Whole-Body Behaviors through Hierarchical Control of Behavioral Primitives , 2005, Int. J. Humanoid Robotics.
[25] Jakub W. Pachocki,et al. Learning dexterous in-hand manipulation , 2018, Int. J. Robotics Res..
[26] Yuval Tassa,et al. Maximum a Posteriori Policy Optimisation , 2018, ICLR.
[27] Sergey Levine,et al. (CAD)$^2$RL: Real Single-Image Flight without a Single Real Image , 2016, Robotics: Science and Systems.
[28] Sergey Levine,et al. MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies , 2019, NeurIPS.
[29] Maja J. Mataric,et al. Automated derivation of behavior vocabularies for autonomous humanoid motion , 2003, AAMAS '03.
[30] Nando de Freitas,et al. Reinforcement and Imitation Learning for Diverse Visuomotor Skills , 2018, Robotics: Science and Systems.
[31] Aude Billard,et al. Reinforcement learning for imitating constrained reaching movements , 2007, Adv. Robotics.
[32] Sergey Levine,et al. Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations , 2017, Robotics: Science and Systems.
[33] Stefan Schaal,et al. 2008 Special Issue: Reinforcement learning of motor skills with policy gradients , 2008 .
[34] Sergey Levine,et al. DeepMimic , 2018, ACM Trans. Graph..
[35] Alberto Rodriguez,et al. TossingBot: Learning to Throw Arbitrary Objects With Residual Physics , 2019, IEEE Transactions on Robotics.
[36] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[37] Sergey Levine,et al. Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection , 2016, Int. J. Robotics Res..
[38] Leslie Pack Kaelbling,et al. Effective reinforcement learning for mobile robots , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).
[39] Stefano Ermon,et al. Generative Adversarial Imitation Learning , 2016, NIPS.
[40] Andrew Y. Ng,et al. Pharmacokinetics of a novel formulation of ivermectin after administration to goats , 2000, ICML.
[41] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[42] Stefan Schaal,et al. Skill learning and task outcome prediction for manipulation , 2011, 2011 IEEE International Conference on Robotics and Automation.
[43] Yuval Tassa,et al. Learning and Transfer of Modulated Locomotor Controllers , 2016, ArXiv.
[44] Yuval Tassa,et al. Emergence of Locomotion Behaviours in Rich Environments , 2017, ArXiv.
[45] Stefan Schaal,et al. Learning from Demonstration , 1996, NIPS.
[46] Nicolas Heess,et al. Hierarchical visuomotor control of humanoids , 2018, ICLR.
[47] Pieter Abbeel,et al. Learning for control from multiple demonstrations , 2008, ICML '08.
[48] Martin A. Riedmiller,et al. Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards , 2017, ArXiv.
[49] Glen Berseth,et al. Terrain-adaptive locomotion skills using deep reinforcement learning , 2016, ACM Trans. Graph..
[50] Shane Legg,et al. IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures , 2018, ICML.
[51] Yee Whye Teh,et al. Neural probabilistic motor primitives for humanoid control , 2018, ICLR.
[52] Kazuya Otani,et al. Adaptive whole-body manipulation in human-to-humanoid multi-contact motion retargeting , 2017, 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids).