Reinforcement Learning

Policy Certificates: Towards Accountable Reinforcement Learning ICML 2019 Policy Consolidation for Continual Reinforcement Learning ICML 2019 Policy Continuation with Hindsight Inverse Dynamics NeurIPS 2019 Policy Learning for Fairness in Ranking NeurIPS 2019 Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games NeurIPS 2019 Policy Optimization with Model-Based Explorations AAAI 2019 Policy Poisoning in Batch Reinforcement Learning and Control NeurIPS 2019 POLITEX: Regret Bounds for Policy Iteration using Expert Prediction ICML 2019 Posterior-regularized REINFORCE for Instance Selection in Distant Supervision NAACL 2019 Predictor-Corrector Policy Optimization ICML 2019 Privacy-Preserving Q-Learning with Functional Noise in Continuous Spaces NeurIPS 2019 Probabilistic Planning with Sequential Monte Carlo methods ICLR 2019 Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning ICLR 2019 Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning ICML 2019 Projections for Approximate Policy Iteration Algorithms ICML 2019 ProMP: Proximal Meta-Policy Search ICLR 2019 Propagating Uncertainty in Reinforcement Learning via Wasserstein Barycenters NeurIPS 2019 Provably Efficient Imitation Learning from Observation Alone ICML 2019 Provably Efficient Maximum Entropy Exploration ICML 2019 Provably Efficient Q-learning with Function Approximation via Distribution Shift Error Checking Oracle NeurIPS 2019 Provably Efficient Q-Learning with Low Switching Cost NeurIPS 2019 Provably Global Convergence of Actor-Critic: A Case for Linear Quadratic Regulator with Ergodic Cost NeurIPS 2019 Provably Robust Blackbox Optimization for Reinforcement Learning CoRL 2019 Pun-GAN: Generative Adversarial Network for Pun Generation EMNLP 2019 PyRoboLearn: A Python Framework for Robot Learning Practitioners CoRL 2019