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Deep RL

3861 directly classified papers

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Papers

The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously CORL 2017
Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning CORL 2017
True Online Temporal-Difference Learning JMLR 2016
Recurrent Attention Models for Depth-Based Person Identification CVPR 2016
Model-Free Trajectory Optimization for Reinforcement Learning ICML 2016
Continuous Deep Q-Learning with Model-based Acceleration ICML 2016
An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning JMLR 2016
Control of Memory, Active Perception, and Action in Minecraft ICML 2016
Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control ICML 2016
Benchmarking Deep Reinforcement Learning for Continuous Control ICML 2016
Learning Simple Algorithms from Examples ICML 2016
Addressing Environment Non-Stationarity by Repeating Q-learning Updates JMLR 2016
Practical Kernel-Based Reinforcement Learning JMLR 2016
Tree-Structured Reinforcement Learning for Sequential Object Localization NIPS 2016
Deep Exploration via Bootstrapped DQN NIPS 2016
Safe and Efficient Off-Policy Reinforcement Learning NIPS 2016
Generative Adversarial Imitation Learning NIPS 2016
Linear Feature Encoding for Reinforcement Learning NIPS 2016
Asynchronous Methods for Deep Reinforcement Learning ICML 2016
Dueling Network Architectures for Deep Reinforcement Learning ICML 2016
VIME: Variational Information Maximizing Exploration NIPS 2016
Unifying Count-Based Exploration and Intrinsic Motivation NIPS 2016
Value Iteration Networks NIPS 2016
Strategic Attentive Writer for Learning Macro-Actions NIPS 2016
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation NIPS 2016