deep reinforcement learning

Learning how to Active Learn: A Deep Reinforcement Learning Approach EMNLP 2017 Learning to Diagnose: Assimilating Clinical Narratives using Deep Reinforcement Learning IJCNLP 2017 Learning what to read: Focused machine reading EMNLP 2017 Modular Multitask Reinforcement Learning with Policy Sketches ICML 2017 Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments NeurIPS 2017 Multi-Task Deep Reinforcement Learning for Continuous Action Control IJCAI 2017 Neural Episodic Control ICML 2017 Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes NeurIPS 2017 Runtime Neural Pruning NeurIPS 2017 Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation NeurIPS 2017 Sentence Simplification with Deep Reinforcement Learning EMNLP 2017 Shallow Updates for Deep Reinforcement Learning NeurIPS 2017 Sim-to-Real Robot Learning from Pixels with Progressive Nets CoRL 2017 Speeding up Reinforcement Learning-based Information Extraction Training using Asynchronous Methods EMNLP 2017 Tactics of Adversarial Attack on Deep Reinforcement Learning Agents IJCAI 2017 The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously CoRL 2017 Thinking Fast and Slow with Deep Learning and Tree Search NeurIPS 2017 Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning CoRL 2017 Value Prediction Network NeurIPS 2017 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 Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation NeurIPS 2016 Interactive Spoken Content Retrieval by Deep Reinforcement Learning Interspeech 2016