Policy Learning

CUP: Critic-Guided Policy Reuse NeurIPS 2022 Curriculum Reinforcement Learning via Constrained Optimal Transport ICML 2022 Data augmentation for efficient learning from parametric experts NeurIPS 2022 Data-Efficient Model Learning for Control with Jacobian-Regularized Dynamic-Mode Decomposition CoRL 2022 Decentralized Cooperative Reinforcement Learning with Hierarchical Information Structure ALT 2022 Deep Whole-Body Control: Learning a Unified Policy for Manipulation and Locomotion CoRL 2022 Defining and Characterizing Reward Gaming NeurIPS 2022 Delayed Reinforcement Learning by Imitation ICML 2022 Deterministic policy gradient: Convergence analysis UAI 2022 Difference Advantage Estimation for Multi-Agent Policy Gradients ICML 2022 Differentially Private Regret Minimization in Episodic Markov Decision Processes AAAI 2022 Dimensionality Reduction and Prioritized Exploration for Policy Search AISTATS 2022 Discovered Policy Optimisation NeurIPS 2022 Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning NeurIPS 2022 Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning ICML 2022 Disentangling Transfer in Continual Reinforcement Learning NeurIPS 2022 Distillation of RL Policies with Formal Guarantees via Variational Abstraction of Markov Decision Processes AAAI 2022 Distributional Reinforcement Learning for Risk-Sensitive Policies NeurIPS 2022 Divergence-Regularized Multi-Agent Actor-Critic ICML 2022 DNA: Proximal Policy Optimization with a Dual Network Architecture NeurIPS 2022 Do Differentiable Simulators Give Better Policy Gradients? ICML 2022 Dynamic Dialogue Policy for Continual Reinforcement Learning COLING 2022 Dynamics-Aware Comparison of Learned Reward Functions ICLR 2022 Efficient Reinforcement Learning with Prior Causal Knowledge CLeaR 2022 Efficient Risk-Averse Reinforcement Learning NeurIPS 2022