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bellman operator

29 papers

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Co-occurring keywords

reinforcement learning (4352) markov decision process (790) value iteration (162) distributional reinforcement learning (72) offline reinforcement learning (492) value function (295) policy optimization (657) off-policy learning (228) value function approximation (100) sample complexity (1169)

Papers

Provably Safe Offline-to-Online RL: Decoupling Learning from Data-Driven Safety Enforcement ACL 2026
Epistemic Bellman Operators AAAI 2025
Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces NIPS 2024
Parameterized Projected Bellman Operator AAAI 2024
POCE: Primal Policy Optimization with Conservative Estimation for Multi-constraint Offline Reinforcement Learning CVPR 2024
Simultaneously Updating All Persistence Values in Reinforcement Learning AAAI 2023
Accelerating Value Iteration with Anchoring NIPS 2023
When is Realizability Sufficient for Off-Policy Reinforcement Learning? ICML 2023
Provably Efficient Offline Reinforcement Learning for Partially Observable Markov Decision Processes ICML 2022
Distributional Reinforcement Learning for Risk-Sensitive Policies NIPS 2022
Reinforcement Learning from Partial Observation: Linear Function Approximation with Provable Sample Efficiency ICML 2022
Approximate Value Equivalence NIPS 2022
On the Estimation Bias in Double Q-Learning NIPS 2021
Distributional Reinforcement Learning via Moment Matching AAAI 2021
Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators NIPS 2021
Proper Value Equivalence NIPS 2021
Provable Benefits of Actor-Critic Methods for Offline Reinforcement Learning NIPS 2021
Bayesian Bellman Operators NIPS 2021
Fast Algorithms for $L_\infty$-constrained S-rectangular Robust MDPs NIPS 2021
Value Function in Frequency Domain and the Characteristic Value Iteration Algorithm NIPS 2019
Limiting Extrapolation in Linear Approximate Value Iteration NIPS 2019
A Family of Robust Stochastic Operators for Reinforcement Learning NIPS 2019
Planning in entropy-regularized Markov decision processes and games NIPS 2019
A Theory of Regularized Markov Decision Processes ICML 2019
An Analysis of Categorical Distributional Reinforcement Learning AISTATS 2018