off-policy learning

Data-Efficient Hierarchical Reinforcement Learning NeurIPS 2018 Distributed Distributional Deterministic Policy Gradients ICLR 2018 Evolution-Guided Policy Gradient in Reinforcement Learning NeurIPS 2018 Learning by Playing Solving Sparse Reward Tasks from Scratch ICML 2018 Learning to Explore via Meta-Policy Gradient ICML 2018 Maximum a Posteriori Policy Optimisation ICLR 2018 M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search NeurIPS 2018 On Generalized Bellman Equations and Temporal-Difference Learning JMLR 2018 Parameter Space Noise for Exploration ICLR 2018 QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning ICML 2018 Reinforcement Learning Algorithm Selection ICLR 2018 Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor ICML 2018 The Reactor: A fast and sample-efficient Actor-Critic agent for Reinforcement Learning ICLR 2018 Trust-PCL: An Off-Policy Trust Region Method for Continuous Control ICLR 2018 Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning ICML 2018 Variance Regularized Counterfactual Risk Minimization via Variational Divergence Minimization ICML 2018 DART: Noise Injection for Robust Imitation Learning CoRL 2017 Hindsight Experience Replay NeurIPS 2017 Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning NeurIPS 2017 Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control ICML 2017 An Emphatic Approach to the Problem of Off-policy Temporal-Difference Learning JMLR 2016 Safe and Efficient Off-Policy Reinforcement Learning NeurIPS 2016 Weak Convergence Properties of Constrained Emphatic Temporal-difference Learning with Constant and Slowly Diminishing Stepsize JMLR 2016 Off-policy Model-based Learning under Unknown Factored Dynamics ICML 2015 On Convergence of Emphatic Temporal-Difference Learning COLT 2015