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Deep RL

3,886 papers

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Papers

CAD2RL: Real Single-Image Flight Without a Single Real Image RSS 2017
Preparing for the Unknown: Learning a Universal Policy with Online System Identification RSS 2017
Improving PAC Exploration Using the Median Of Means NIPS 2016
PAC Reinforcement Learning with Rich Observations NIPS 2016
Learning values across many orders of magnitude NIPS 2016
Tree-Structured Reinforcement Learning for Sequential Object Localization NIPS 2016
Linear Feature Encoding for Reinforcement Learning NIPS 2016
Deep Exploration via Bootstrapped DQN NIPS 2016
VIME: Variational Information Maximizing Exploration NIPS 2016
Unifying Count-Based Exploration and Intrinsic Motivation NIPS 2016
Value Iteration Networks NIPS 2016
Safe and Efficient Off-Policy Reinforcement Learning NIPS 2016
Strategic Attentive Writer for Learning Macro-Actions NIPS 2016
Generative Adversarial Imitation Learning NIPS 2016
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation NIPS 2016
Generating Long-term Trajectories Using Deep Hierarchical Networks NIPS 2016
Recurrent Attention Models for Depth-Based Person Identification CVPR 2016
Reinforcement Learning for Visual Object Detection CVPR 2016
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization ICML 2016
Learning Simple Algorithms from Examples ICML 2016
Benchmarking Deep Reinforcement Learning for Continuous Control ICML 2016
Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control ICML 2016
Opponent Modeling in Deep Reinforcement Learning ICML 2016
Graying the black box: Understanding DQNs ICML 2016
Asynchronous Methods for Deep Reinforcement Learning ICML 2016