暂无分享,去创建一个
[1] D. Floreano,et al. Evolutionary Robotics: The Biology,Intelligence,and Technology , 2000 .
[2] András Lörincz,et al. MDPs: Learning in Varying Environments , 2003, J. Mach. Learn. Res..
[3] Javier Ruiz-del-Solar,et al. Back to reality: Crossing the reality gap in evolutionary robotics , 2004 .
[4] Pieter Abbeel,et al. Exploration and apprenticeship learning in reinforcement learning , 2005, ICML.
[5] Hod Lipson,et al. Nonlinear system identification using coevolution of models and tests , 2005, IEEE Transactions on Evolutionary Computation.
[6] Pieter Abbeel,et al. Using inaccurate models in reinforcement learning , 2006, ICML.
[7] Michel Gevers,et al. System identification without Lennart Ljung : what would have been different ? , 2006 .
[8] Stéphane Doncieux,et al. Crossing the reality gap in evolutionary robotics by promoting transferable controllers , 2010, GECCO '10.
[9] Carl E. Rasmussen,et al. PILCO: A Model-Based and Data-Efficient Approach to Policy Search , 2011, ICML.
[10] J. Andrew Bagnell,et al. Agnostic System Identification for Model-Based Reinforcement Learning , 2012, ICML.
[11] Bruno Castro da Silva,et al. Learning Parameterized Skills , 2012, ICML.
[12] Olivier Sigaud,et al. Learning compact parameterized skills with a single regression , 2013, 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids).
[13] Guy Lever,et al. Deterministic Policy Gradient Algorithms , 2014, ICML.
[14] Emanuel Todorov,et al. Ensemble-CIO: Full-body dynamic motion planning that transfers to physical humanoids , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[15] Sehoon Ha,et al. Reducing hardware experiments for model learning and policy optimization , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[16] Sergey Levine,et al. Trust Region Policy Optimization , 2015, ICML.
[17] Pieter Abbeel,et al. Deep learning helicopter dynamics models , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[18] David Silver,et al. Memory-based control with recurrent neural networks , 2015, ArXiv.
[19] Nolan Wagener,et al. Learning contact-rich manipulation skills with guided policy search , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).
[20] Shane Legg,et al. Human-level control through deep reinforcement learning , 2015, Nature.
[21] Yuval Tassa,et al. Continuous control with deep reinforcement learning , 2015, ICLR.
[22] Wojciech Zaremba,et al. Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model , 2016, ArXiv.
[23] Alex Graves,et al. Asynchronous Methods for Deep Reinforcement Learning , 2016, ICML.
[24] Stephen James,et al. 3D Simulation for Robot Arm Control with Deep Q-Learning , 2016, ArXiv.
[25] Sergey Levine,et al. End-to-End Training of Deep Visuomotor Policies , 2015, J. Mach. Learn. Res..
[26] Glen Berseth,et al. Terrain-adaptive locomotion skills using deep reinforcement learning , 2016, ACM Trans. Graph..
[27] Sergey Levine,et al. High-Dimensional Continuous Control Using Generalized Advantage Estimation , 2015, ICLR.
[28] Abhinav Gupta,et al. Supersizing self-supervision: Learning to grasp from 50K tries and 700 robot hours , 2015, 2016 IEEE International Conference on Robotics and Automation (ICRA).
[29] Razvan Pascanu,et al. Sim-to-Real Robot Learning from Pixels with Progressive Nets , 2016, CoRL.
[30] Sergey Levine,et al. Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic , 2016, ICLR.
[31] Balaraman Ravindran,et al. EPOpt: Learning Robust Neural Network Policies Using Model Ensembles , 2016, ICLR.
[32] Angela P. Schoellig,et al. High-precision trajectory tracking in changing environments through L1 adaptive feedback and iterative learning , 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA).
[33] Sergey Levine,et al. Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection , 2016, Int. J. Robotics Res..
[34] Siddhartha S. Srinivasa,et al. DART: Dynamic Animation and Robotics Toolkit , 2018, J. Open Source Softw..