conftrace_

value iteration

162 papers

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Also known as

VI

Co-occurring keywords

reinforcement learning (4352) markov decision process (790) regret bound (1926) offline reinforcement learning (492) function approximation (319) dynamic programming (274) policy iteration (99) sample complexity (1169) model-based reinforcement learning (415) policy learning (702)

Papers

Self-Paced Context Evaluation for Contextual Reinforcement Learning ICML 2021
Abstract Value Iteration for Hierarchical Reinforcement Learning AISTATS 2021
Robust Value Iteration for Continuous Control Tasks RSS 2021
Quantum algorithms for reinforcement learning with a generative model ICML 2021
Is Pessimism Provably Efficient for Offline RL? ICML 2021
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration AAAI 2021
Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL NIPS 2021
Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization NIPS 2021
Partial Policy Iteration for L1-Robust Markov Decision Processes JMLR 2021
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game ICML 2021
Finding the Stochastic Shortest Path with Low Regret: the Adversarial Cost and Unknown Transition Case ICML 2021
Expected Eligibility Traces AAAI 2021
Reconciling Rewards with Predictive State Representations IJCAI 2021
Exponential Lower Bounds for Planning in MDPs With Linearly-Realizable Optimal Action-Value Functions ALT 2021
Solving Partially Observable Stochastic Shortest-Path Games IJCAI 2021
When to stop value iteration: stability and near-optimality versus computation L4DC 2021
Fast Approximate Dynamic Programming for Infinite-Horizon Markov Decision Processes NIPS 2021
No-Press Diplomacy from Scratch NIPS 2021
Universal Value Iteration Networks: When Spatially-Invariant Is Not Universal AAAI 2020
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes AAAI 2020
Static and Dynamic Values of Computation in MCTS UAI 2020
Multi-Agent Routing Value Iteration Network ICML 2020
Reward-Free Exploration for Reinforcement Learning ICML 2020
Multi-step Greedy Reinforcement Learning Algorithms ICML 2020
Learning Near Optimal Policies with Low Inherent Bellman Error ICML 2020