Reinforcement Learning

Generating Long-term Trajectories Using Deep Hierarchical Networks NeurIPS 2016 Generative Adversarial Imitation Learning NeurIPS 2016 Geometric Swimming on a Granular Surface RSS 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 Decision Making In Electricity Grid Management ICML 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 Interactive Spoken Content Retrieval by Deep Reinforcement Learning Interspeech 2016 Kernel Estimation and Model Combination in A Bandit Problem with Covariates JMLR 2016 Learning Multiagent Communication with Backpropagation NeurIPS 2016 Learning Simple Algorithms from Examples ICML 2016 Learning the Variance of the Reward-To-Go JMLR 2016 Learning to Communicate with Deep Multi-Agent Reinforcement Learning NeurIPS 2016 Learning values across many orders of magnitude NeurIPS 2016 Lenient Learning in Independent-Learner Stochastic Cooperative Games JMLR 2016 Linear Feature Encoding for Reinforcement Learning NeurIPS 2016 Model-Free Imitation Learning with Policy Optimization ICML 2016 Model-Free Trajectory Optimization for Reinforcement Learning ICML 2016 Multi-Objective Markov Decision Processes for Data-Driven Decision Support JMLR 2016 Near Optimal Behavior via Approximate State Abstraction ICML 2016 Online Relative Entropy Policy Search using Reproducing Kernel Hilbert Space Embeddings AISTATS 2016 Only H is left: Near-tight Episodic PAC RL NeurIPS 2016