policy evaluation
Policy evaluation is a process in reinforcement learning where the performance of a given policy is assessed, often through simulations or empirical testing, to determine its effectiveness in achieving desired outcomes.
- Causal Explanation-Guided Learning for Organ Allocation
- Conformal Prediction Beyond the Horizon: Distribution-Free Inference for Policy Evaluation
- Finite Sample Analysis of Linear Temporal Difference Learning with Arbitrary Features
- Finite-Sample Analysis of Policy Evaluation for Robust Average Reward Reinforcement Learning
- Non-rectangular Robust MDPs with Normed Uncertainty Sets
- ReSim: Reliable World Simulation for Autonomous Driving
- State Entropy Regularization for Robust Reinforcement Learning
- State Entropy Regularization for Robust Reinforcement Learning
- Towards Provable Emergence of In-Context Reinforcement Learning