Methods

A Stochastic Model for Computer-Aided Human-Human Dialogue Interspeech 2016 Asynchronous Methods for Deep Reinforcement Learning ICML 2016 Bayesian Policy Gradient and Actor-Critic Algorithms JMLR 2016 Benchmarking Deep Reinforcement Learning for Continuous Control ICML 2016 Black-Box Policy Search with Probabilistic Programs AISTATS 2016 Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning NeurIPS 2016 Combined Optimization and Reinforcement Learning for Manipulation Skills RSS 2016 Continuous Deep Q-Learning with Model-based Acceleration ICML 2016 Control of Memory, Active Perception, and Action in Minecraft ICML 2016 Cooperative Inverse Reinforcement Learning NeurIPS 2016 Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control ICML 2016 Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning ICML 2016 Deep Exploration via Bootstrapped DQN NeurIPS 2016 Differentially Private Policy Evaluation ICML 2016 Doubly Robust Off-policy Value Evaluation for Reinforcement Learning ICML 2016 Dueling Network Architectures for Deep Reinforcement Learning ICML 2016 Generalization and Exploration via Randomized Value Functions ICML 2016 Generating Long-term Trajectories Using Deep Hierarchical Networks NeurIPS 2016 Generative Adversarial Imitation Learning NeurIPS 2016 Graying the black box: Understanding DQNs ICML 2016 Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization ICML 2016 Guided Policy Search via Approximate Mirror Descent NeurIPS 2016 Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation NeurIPS 2016 Hierarchical Relative Entropy Policy Search JMLR 2016 Improving PAC Exploration Using the Median Of Means NeurIPS 2016