← Applications
Reinforcement Learning › Applications ›

Value Iteration

306 directly classified papers

Papers per year

Papers

How Private Is Your RL Policy? An Inverse RL Based Analysis Framework AAAI 2022
Towards Real-World Navigation With Deep Differentiable Planners CVPR 2022
Generalised Policy Improvement with Geometric Policy Composition ICML 2022
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes ICML 2022
Improved Regret for Differentially Private Exploration in Linear MDP ICML 2022
Distributionally Robust $Q$-Learning ICML 2022
Model-Value Inconsistency as a Signal for Epistemic Uncertainty ICML 2022
Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer ICML 2022
Spending Thinking Time Wisely: Accelerating MCTS with Virtual Expansions NIPS 2022
Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach JMLR 2022
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets NIPS 2022
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation AAAI 2022
Evaluating the perceived safety of urban city via maximum entropy deep inverse reinforcement learning ACML 2022
Value Refinement Network (VRN) IJCAI 2022
Empirical Gateaux Derivatives for Causal Inference NIPS 2022
Continuous Deep Q-Learning in Optimal Control Problems: Normalized Advantage Functions Analysis NIPS 2022
DeepTOP: Deep Threshold-Optimal Policy for MDPs and RMABs NIPS 2022
PID Accelerated Value Iteration Algorithm ICML 2021
Self-Paced Context Evaluation for Contextual Reinforcement Learning ICML 2021
Universal Off-Policy Evaluation NIPS 2021
Reward is enough for convex MDPs NIPS 2021
Minimax Regret for Stochastic Shortest Path NIPS 2021
Abstract Value Iteration for Hierarchical Reinforcement Learning AISTATS 2021
No-Press Diplomacy from Scratch NIPS 2021
Monte Carlo Tree Search With Iteratively Refining State Abstractions NIPS 2021