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Policy Learning

2068 directly classified papers

Papers per year

Papers

Receding Horizon Inverse Reinforcement Learning NIPS 2022
A Hierarchical Bayesian Approach to Inverse Reinforcement Learning with Symbolic Reward Machines ICML 2022
Actor-Critic based Improper Reinforcement Learning ICML 2022
Exponential Family Model-Based Reinforcement Learning via Score Matching NIPS 2022
Regularizing a Model-based Policy Stationary Distribution to Stabilize Offline Reinforcement Learning ICML 2022
Robust Policy Learning over Multiple Uncertainty Sets ICML 2022
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee ICML 2022
Understanding Policy Gradient Algorithms: A Sensitivity-Based Approach ICML 2022
Robust Anytime Learning of Markov Decision Processes NIPS 2022
Policy Gradient Method For Robust Reinforcement Learning ICML 2022
The Geometry of Robust Value Functions ICML 2022
Safe Exploration for Efficient Policy Evaluation and Comparison ICML 2022
Reward-Free RL is No Harder Than Reward-Aware RL in Linear Markov Decision Processes ICML 2022
A Temporal-Difference Approach to Policy Gradient Estimation ICML 2022
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses ICML 2022
Generalised Policy Improvement with Geometric Policy Composition ICML 2022
Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments ICML 2022
A Few Expert Queries Suffices for Sample-Efficient RL with Resets and Linear Value Approximation NIPS 2022
Do Differentiable Simulators Give Better Policy Gradients? ICML 2022
Divergence-Regularized Multi-Agent Actor-Critic ICML 2022
Saute RL: Almost Surely Safe Reinforcement Learning Using State Augmentation ICML 2022
Disentangling Sources of Risk for Distributional Multi-Agent Reinforcement Learning ICML 2022
Communicating via Markov Decision Processes ICML 2022
Contrastive UCB: Provably Efficient Contrastive Self-Supervised Learning in Online Reinforcement Learning ICML 2022
Optimal Estimation of Policy Gradient via Double Fitted Iteration ICML 2022