bayesian reinforcement learning

Cache-Efficient Posterior Sampling for Reinforcement Learning with LLM-Derived Priors Across Discrete and Continuous Domains EMNLP 2025 Bayesian Exploration Networks ICML 2024 Value-Distributional Model-Based Reinforcement Learning JMLR 2024 Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach AISTATS 2023 Surveillance Evasion Through Bayesian Reinforcement Learning AISTATS 2023 Bayesian Reinforcement Learning for Single-Episode Missions in Partially Unknown Environments CoRL 2022 Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees NeurIPS 2022 Regret Bounds for Information-Directed Reinforcement Learning NeurIPS 2022 Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability AAAI 2022 Bayesian Bellman Operators NeurIPS 2021 GaussianPath:A Bayesian Multi-Hop Reasoning Framework for Knowledge Graph Reasoning AAAI 2021 Offline Meta Reinforcement Learning -- Identifiability Challenges and Effective Data Collection Strategies NeurIPS 2021 Bayesian Reinforcement Learning via Deep, Sparse Sampling AISTATS 2020 Inductive-bias-driven Reinforcement Learning For Efficient Schedules in Heterogeneous Clusters ICML 2020 Pessimism About Unknown Unknowns Inspires Conservatism COLT 2020 AC-Teach: A Bayesian Actor-Critic Method for Policy Learning with an Ensemble of Suboptimal Teachers CoRL 2019 Assumed Density Filtering Q-learning IJCAI 2019 Correlation Priors for Reinforcement Learning NeurIPS 2019 Bayesian RL for Goal-Only Rewards CoRL 2018 Constrained Bayesian Reinforcement Learning via Approximate Linear Programming IJCAI 2017 Learning in POMDPs with Monte Carlo Tree Search ICML 2017 Dual Control for Approximate Bayesian Reinforcement Learning JMLR 2016 Cover Tree Bayesian Reinforcement Learning JMLR 2014 ABC Reinforcement Learning ICML 2013 Bayesian Hierarchical Reinforcement Learning NeurIPS 2012