CAD2RL: Real Single-Image Flight without a Single Real Image
Comments To appear at Robotics: Science and Systems Conference (R:SS), 2017. Supplementary video: https://www.youtube.com/watch?v=nXBWmzFrj5s
作者
Sergey Levine
Robotics / Reinforcement Learning
Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning
Adapting Deep Visuomotor Representations with Weak Pairwise Constraints
Trust Region Policy Optimization
Comments 16 pages, ICML 2015
Learning from the Hindsight Plan -- Episodic MPC Improvement
Comments Additional experiments for neural network generalization and for varying the planning horizon. Paper accepted to ICRA 2017
Value Iteration Networks
Comments Fixed missing table values
Journal ref Advances in Neural Information Processing Systems 29 pages 2154--2162, 2016
Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstration
Comments Accepted at International Conference on Intelligent Robots and Systems(IROS) 2016. Pdf file updated for stylistic consistency
Deep Visual Foresight for Planning Robot Motion
Comments ICRA 2017. Supplementary video: https://sites.google.com/site/robotforesight/
Generalizing Skills with Semi-Supervised Reinforcement Learning
Comments ICLR 2017
Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning
Comments Published as a conference paper at ICLR 2017
Deep Reinforcement Learning for Tensegrity Robot Locomotion
Comments International Conference on Robotics and Automation (ICRA), 2017. Project website link is http://rll.berkeley.edu/drl_tensegrity
Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation
Comments 8 pages, accepted to International Conference on Robotics and Automation (ICRA) 2017
EPOpt: Learning Robust Neural Network Policies Using Model Ensembles
Comments Accepted for publication at the International Conference on Learning Representations (ICLR) 2017. Supplementary video: https://youtu.be/w1YJ9vwaoto
Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic
Comments Conference Paper at the International Conference on Learning Representations (ICLR) 2017
PLATO: Policy Learning using Adaptive Trajectory Optimization
Learning to Poke by Poking: Experiential Learning of Intuitive Physics
Journal ref NIPS 2016
Uncertainty-Aware Reinforcement Learning for Collision Avoidance
A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models
Comments NIPS 2016 Workshop on Adversarial Training. First two authors contributed equally
Deep Reinforcement Learning for Robotic Manipulation with Asynchronous Off-Policy Updates
Unsupervised Learning for Physical Interaction through Video Prediction
Comments To appear in NIPS '16; Video results, code, and data available at: http://www.sites.google.com/site/robotprediction
Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial States
Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer
Comments Under review at the International Conference on Robotics and Automation (ICRA) 2017
Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection
Comments This is an extended version of "Learning Hand-Eye Coordination for Robotic Grasping with Large-Scale Data Collection," ISER 2016. Draft modified to correct typo in Algorithm 1 and add a link to the publicly available dataset
One-Shot Learning of Manipulation Skills with Online Dynamics Adaptation and Neural Network Priors
Guided Policy Search as Approximate Mirror Descent
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization
Comments International Conference on Machine Learning (ICML), 2016, to appear
End-to-End Training of Deep Visuomotor Policies
Comments updating with revisions for JMLR final version
Model-based Reinforcement Learning with Parametrized Physical Models and Optimism-Driven Exploration
Comments 8 pages
Deep Spatial Autoencoders for Visuomotor Learning
Comments Published in the International Conference on Robotics and Automation (ICRA)
