Methods

Asynchronous Methods for Model-Based Reinforcement Learning CoRL 2019 A Theory of Regularized Markov Decision Processes ICML 2019 A Tighter Analysis of Randomised Policy Iteration UAI 2019 A Topic-Aware Reinforced Model for Weakly Supervised Stance Detection AAAI 2019 Attention-Aware Sampling via Deep Reinforcement Learning for Action Recognition AAAI 2019 Augmenting Markov Decision Processes with Advising AAAI 2019 A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment NeurIPS 2019 Automatic Face Aging in Videos via Deep Reinforcement Learning CVPR 2019 Automatic Successive Reinforcement Learning with Multiple Auxiliary Rewards IJCAI 2019 Autoregressive Policies for Continuous Control Deep Reinforcement Learning IJCAI 2019 Batch Policy Learning under Constraints ICML 2019 Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning ICML 2019 Bayesian Policy Optimization for Model Uncertainty ICLR 2019 Better Exploration with Optimistic Actor Critic NeurIPS 2019 Better, Faster, Stronger Sequence Tagging Constituent Parsers NAACL 2019 Better Rewards Yield Better Summaries: Learning to Summarise Without References EMNLP 2019 Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs NeurIPS 2019 Biases for Emergent Communication in Multi-agent Reinforcement Learning NeurIPS 2019 Bootstrap Estimated Uncertainty of the Environment Model for Model-Based Reinforcement Learning AAAI 2019 Budgeted Policy Learning for Task-Oriented Dialogue Systems ACL 2019 Budgeted Reinforcement Learning in Continuous State Space NeurIPS 2019 Building Personalized Simulator for Interactive Search IJCAI 2019 Building Task-Oriented Visual Dialog Systems Through Alternative Optimization Between Dialog Policy and Language Generation EMNLP 2019 CAB: Continuous Adaptive Blending for Policy Evaluation and Learning ICML 2019 Calibrated Model-Based Deep Reinforcement Learning ICML 2019