Policy Learning

A Survey of Preference-Based Reinforcement Learning Methods JMLR 2017 Bridging the Gap Between Value and Policy Based Reinforcement Learning NeurIPS 2017 Cold-Start Reinforcement Learning with Softmax Policy Gradient NeurIPS 2017 Compatible Reward Inverse Reinforcement Learning NeurIPS 2017 Composite Task-Completion Dialogue Policy Learning via Hierarchical Deep Reinforcement Learning EMNLP 2017 Constrained Bayesian Reinforcement Learning via Approximate Linear Programming IJCAI 2017 Constrained Policy Optimization ICML 2017 Data-Efficient Policy Evaluation Through Behavior Policy Search ICML 2017 DDCO: Discovery of Deep Continuous Options for Robot Learning from Demonstrations CoRL 2017 Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction ICML 2017 Domain-Independent User Satisfaction Reward Estimation for Dialogue Policy Learning Interspeech 2017 Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions IJCAI 2017 Enabling Robots to Communicate Their Objectives RSS 2017 End-to-End Differentiable Adversarial Imitation Learning ICML 2017 Exploration-Exploitation in MDPs with Options AISTATS 2017 Factorized Asymptotic Bayesian Policy Search for POMDPs IJCAI 2017 Fairness in Reinforcement Learning ICML 2017 FeUdal Networks for Hierarchical Reinforcement Learning ICML 2017 From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood ACL 2017 Hierarchy Through Composition with Multitask LMDPs ICML 2017 I-dual: Solving Constrained SSPs via Heuristic Search in the Dual Space IJCAI 2017 Improving Reinforcement Learning with Confidence-Based Demonstrations IJCAI 2017 Improving Stochastic Policy Gradients in Continuous Control with Deep Reinforcement Learning using the Beta Distribution ICML 2017 InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations NeurIPS 2017 Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning NeurIPS 2017