Policy Learning

Learning Reward Machines for Partially Observable Reinforcement Learning NeurIPS 2019 Learning Robust Options by Conditional Value at Risk Optimization NeurIPS 2019 Learning Self-Imitating Diverse Policies ICLR 2019 Learning the Extraction Order of Multiple Relational Facts in a Sentence with Reinforcement Learning EMNLP 2019 Learning to Ask for Conversational Machine Learning EMNLP 2019 Learning to Generalize from Sparse and Underspecified Rewards ICML 2019 Learning to Understand Goal Specifications by Modelling Reward ICLR 2019 Leveraging Human Guidance for Deep Reinforcement Learning Tasks IJCAI 2019 LexicalAT: Lexical-Based Adversarial Reinforcement Training for Robust Sentiment Classification EMNLP 2019 Logarithmic Regret for Online Control NeurIPS 2019 Logic-Based Sequential Decision-Making AAAI 2019 Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications AAAI 2019 Marginal Policy Gradients: A Unified Family of Estimators for Bounded Action Spaces with Applications ICLR 2019 Maximum Entropy-Regularized Multi-Goal Reinforcement Learning ICML 2019 Maximum Expected Hitting Cost of a Markov Decision Process and Informativeness of Rewards NeurIPS 2019 Meta-Inverse Reinforcement Learning with Probabilistic Context Variables NeurIPS 2019 Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control IJCAI 2019 Model-based Behavioral Cloning with Future Image Similarity Learning CoRL 2019 Model-based RL in Contextual Decision Processes: PAC bounds and Exponential Improvements over Model-free Approaches COLT 2019 Model-Free IRL Using Maximum Likelihood Estimation AAAI 2019 Model-Free Model Reconciliation IJCAI 2019 Monte Carlo Tree Search for Policy Optimization IJCAI 2019 Mo' States Mo' Problems: Emergency Stop Mechanisms from Observation NeurIPS 2019 Multiagent Decision Making For Maritime Traffic Management AAAI 2019 Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies ACL 2019