policy iteration

Partial Policy Iteration for L1-Robust Markov Decision Processes JMLR 2021 Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation AAAI 2021 Robust Reinforcement Learning using Least Squares Policy Iteration with Provable Performance Guarantees ICML 2021 Safe Policy Iteration: A Monotonically Improving Approximate Policy Iteration Approach JMLR 2021 The Value-Improvement Path: Towards Better Representations for Reinforcement Learning AAAI 2021 Twice regularized MDPs and the equivalence between robustness and regularization NeurIPS 2021 A Distributional Analysis of Sampling-Based Reinforcement Learning Algorithms AISTATS 2020 An operator view of policy gradient methods NeurIPS 2020 Deep Conservative Policy Iteration AAAI 2020 Kernel Taylor-Based Value Function Approximation for Continuous-State Markov Decision Processes RSS 2020 Lambda-Policy Iteration with Randomization for Contractive Models with Infinite Policies: Well-Posedness and Convergence L4DC 2020 Learning Dexterous Manipulation from Suboptimal Experts CoRL 2020 Multiagent Rollout and Policy Iteration for POMDP with Application to Multi-Robot Repair Problems CoRL 2020 Multi-step Greedy Reinforcement Learning Algorithms ICML 2020 Reinforcement Learning for Control with Multiple Frequencies NeurIPS 2020 Reinforcement Learning with Combinatorial Actions: An Application to Vehicle Routing NeurIPS 2020 Structured Policy Iteration for Linear Quadratic Regulator ICML 2020 A Theory of Regularized Markov Decision Processes ICML 2019 A Tighter Analysis of Randomised Policy Iteration UAI 2019 Explicitly Coordinated Policy Iteration IJCAI 2019 Finite-time Analysis of Approximate Policy Iteration for the Linear Quadratic Regulator NeurIPS 2019 Learning from a Learner ICML 2019 Model-Free Linear Quadratic Control via Reduction to Expert Prediction AISTATS 2019 POLITEX: Regret Bounds for Policy Iteration using Expert Prediction ICML 2019 Projections for Approximate Policy Iteration Algorithms ICML 2019