Reinforcement Learning

A Fast and Reliable Policy Improvement Algorithm AISTATS 2016 An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning JMLR 2016 A Probabilistic Model of Social Decision Making based on Reward Maximization NeurIPS 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 Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control ICML 2016 Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning ICML 2016 Estimating Maximum Expected Value through Gaussian Approximation ICML 2016 Generalization and Exploration via Randomized Value Functions ICML 2016 Hierarchical Decision Making In Electricity Grid Management ICML 2016 Improving PAC Exploration Using the Median Of Means NeurIPS 2016 Learning Simple Algorithms from Examples ICML 2016 Model-Free Trajectory Optimization for Reinforcement Learning ICML 2016 Near Optimal Behavior via Approximate State Abstraction ICML 2016 On the Use of Non-Stationary Strategies for Solving Two-Player Zero-Sum Markov Games AISTATS 2016 Planning for Autonomous Cars that Leverage Effects on Human Actions RSS 2016 Safe and Efficient Off-Policy Reinforcement Learning NeurIPS 2016 Safe Exploration in Finite Markov Decision Processes with Gaussian Processes NeurIPS 2016 Safe Policy Improvement by Minimizing Robust Baseline Regret NeurIPS 2016 Threshold Learning for Optimal Decision Making NeurIPS 2016 Tree-Structured Reinforcement Learning for Sequential Object Localization NeurIPS 2016 A Deeper Look at Planning as Learning from Replay ICML 2015 A Relative Exponential Weighing Algorithm for Adversarial Utility-based Dueling Bandits ICML 2015 Data Generation as Sequential Decision Making NeurIPS 2015