Deep RL

Speeding up Reinforcement Learning-based Information Extraction Training using Asynchronous Methods EMNLP 2017 Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning ICML 2017 Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency Parsing EACL 2017 Tactics of Adversarial Attack on Deep Reinforcement Learning Agents IJCAI 2017 Teaching Machines to Describe Images with Natural Language Feedback NeurIPS 2017 Tensor Based Knowledge Transfer Across Skill Categories for Robot Control IJCAI 2017 The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously CoRL 2017 Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning CoRL 2017 Unifying PAC and Regret: Uniform PAC Bounds for Episodic Reinforcement Learning NeurIPS 2017 Value-Aware Loss Function for Model-based Reinforcement Learning AISTATS 2017 Value Iteration Networks IJCAI 2017 Value Prediction Network NeurIPS 2017 Weighted Double Q-learning IJCAI 2017 Why is Posterior Sampling Better than Optimism for Reinforcement Learning? ICML 2017 Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning ICML 2017 Addressing Environment Non-Stationarity by Repeating Q-learning Updates JMLR 2016 An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning JMLR 2016 Asynchronous Methods for Deep Reinforcement Learning ICML 2016 Benchmarking Deep Reinforcement Learning for Continuous Control ICML 2016 Continuous Deep Q-Learning with Model-based Acceleration ICML 2016 Control of Memory, Active Perception, and Action in Minecraft ICML 2016 Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control ICML 2016 Deep Exploration via Bootstrapped DQN NeurIPS 2016 Dueling Network Architectures for Deep Reinforcement Learning ICML 2016 Generating Long-term Trajectories Using Deep Hierarchical Networks NeurIPS 2016