Markov Decision Processes

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Period ending 2026-09-21

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  1. Beyond Bellman: High-Order Generator Regression for Continuous-Time Policy Evaluation

    Apr 21, 2026Yaowei Zheng, Richong Zhang, Shenxi Wu +5Bellman EquationBackward Induction

  2. StepPO: Step-Aligned Policy Optimization for Agentic Reinforcement Learning

    Apr 20, 2026Daoyu Wang, Qingchuan Li, Mingyue Cheng +4Agentic Reinforcement-Learning FrameworkMarkov Decision Processes

  3. Scale-free adaptive planning for deterministic dynamics & discounted rewards

    Apr 20, 2026Peter L. Bartlett, Victor Gabillon, Jennifer Healey +1Value FunctionsPlanning Methods

  4. Physics-Informed Causal MDPs for Sequential Constraint Repair in Engineering Simulation Pipelines

    Apr 20, 2026Chuhan QiaoStructural Causal ModelMarkov Decision Processes

  5. Beyond the Bellman Fixed Point: Geometry and Fast Policy Identification in Value Iteration

    Apr 19, 2026Donghwan LeeBellman EquationValue Functions

  6. Active World-Model with 4D-informed Retrieval for Exploration and Awareness

    Apr 17, 2026Elaheh Vaezpour, Amirhosein Javadi, Tara JavidiWorld ModelsAutonomous Exploration Strategies

  7. DARLING: Detection Augmented Reinforcement Learning with Non-Stationary Guarantees

    Apr 17, 2026Argyrios Gerogiannis, Yu-Han Huang, Venugopal V. VeeravalliModel-Free Reinforcement LearningMarkov Decision Processes

  8. Sample Complexity Bounds for Stochastic Shortest Path with a Generative Model

    Apr 17, 2026Jean Tarbouriech, Matteo Pirotta, Michal Valko +1Optimal PoliciesShortest Paths

  9. The Price of Paranoia: Robust Risk-Sensitive Cooperation in Non-Stationary Multi-Agent Reinforcement Learning

    Apr 17, 2026Deep Kumar Ganguly, Chandradithya S Jonnalagadda, Pratham Chintamani +1CooperationMulti-Agent Reinforcement Learning

  10. Blazing the trails before beating the path: Sample-efficient Monte-Carlo planning

    Apr 16, 2026Jean-Bastien Grill, Michal Valko, Rémi MunosMarkov Decision ProcessesClassical Planning

  11. POMDP-based Object Search with Growing State Space and Hybrid Action Domain

    Apr 16, 2026Yongbo Chen, Hesheng Wang, Shoudong Huang +1Partially Observable Markov Decision ProcessRobotics

  12. When Can You Poison Rewards? A Tight Characterization of Reward Poisoning in Linear MDPs

    Apr 11, 2026Jose Efraim Aguilar Escamilla, Haoyang Hong, Jiawei Li +4Reward ModelingMarkov Decision Processes

  13. Value Mirror Descent for Reinforcement Learning

    Apr 7, 2026Zhichao Jia, Guanghui LanMirror DescentValue Functions

  14. Resilient Decentralized Ergodic Coverage for Scalable Multi-Robot Systems in Unknown Time-Varying Environments

    Apr 5, 2026Maria G. Mendoza, Victoria Marie Tuck, Chinmay Maheshwari +1Multi-Robot SystemsFinite-Sample Coverage Guarantees

  15. Learning to Learn-at-Test-Time: Language Agents with Learnable Adaptation Policies

    Apr 1, 2026Zhanzhi Lou, Hui Chen, Yibo Li +2Optimal PoliciesSingle-Agent Baselines

  16. Separation is Optimal for LQR under Intermittent Feedback

    Mar 29, 2026Abdullah Y. Etcibasi, C. Emre Koksal, Eylem EkiciLinear Quadratic RegulatorOptimal Policies

  17. End-to-End Efficient RL for Linear Bellman Complete MDPs with Deterministic Transitions

    Mar 24, 2026Zakaria Mhammedi, Alexander Rakhlin, Nneka OkoloMarkov Decision ProcessesOptimal Policies

  18. Calculating Mutual Information between a Reward Maximizer and its Environment

    Feb 13, 2026Alfred Harwood, Jose Faustino, Alex AltairOptimal PoliciesMutual Information

  19. Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity

    Feb 3, 2026Aneri Muni, Vincent Taboga, Esther Derman +2Conditional-Value-At-RiskBellman Equation

  20. Data- and Variance-dependent Regret Bounds for Online Tabular MDPs

    Feb 2, 2026Mingyi Li, Taira Tsuchiya, Kenji YamanishiNear-Optimal Regret GuaranteesMarkov Decision Processes

  21. Meta-Learning-Assisted Constraint Relaxation for Constrained Black-Box Optimization

    Jan 31, 2026Sijie Ma, Zeyuan Ma, Yue-Jiao Gong +1Black-Box OptimizationOptimal Policies

  22. Toward Learning POMDPs Beyond Full-Rank Actions and State Observability

    Jan 26, 2026Seiji Shaw, Travis Manderson, Chad Kessens +1Partially Observable Markov Decision ProcessMarkov Decision Processes

  23. A Probabilistic Approach to Trajectory-Based Optimal Experimental Design

    Jan 16, 2026Ahmed AttiaBayesian Experimental DesignTrajectory Optimization

  24. Precision autotuning for linear solvers via contextual bandit-based RL

    Jan 2, 2026Erin Carson, Xinye ChenSpectral PreconditioningFull-Precision Performance

  25. Soft Fitted Q-Iteration without Bellman Completeness: Occupancy Reweighting and Temperature Annealing

    Dec 30, 2025Lars van der Laan, Nathan KallusBellman EquationOffline Reinforcement Learning

  26. Fitted Q-Evaluation without Bellman Completeness via Occupancy Weighting

    Dec 29, 2025Lars van der Laan, Nathan KallusValue FunctionsBellman Equation

  27. Statistical analysis of Inverse Entropy-regularized Reinforcement Learning

    Dec 7, 2025Denis Belomestny, Alexey Naumov, Artemy Rubtsov +1Entropy Regularized Reinforcement LearningOptimal Policies

  28. Policy Stability for Measuring Operational Performance in Task Assignment with Time-Windows Under Internal Adversarial Influence

    Nov 7, 2025Roee M. Francos, Daniel Garces, Orhan Eren Akgün +1Vehicle Routing ProblemStochastic Delays

  29. Learnable Mixed Nash Equilibria are Collectively Rational

    Oct 16, 2025Geelon So, Yi-An MaNash EquilibriumEquilibrium

  30. Best-of-Both Worlds for linear contextual bandits with paid observations

    Oct 8, 2025Nathan Boyer, Dorian Baudry, Patrick RebeschiniLinear Contextual BanditsPartially Observable Markov Decision Process

  31. Finite-Time Convergence of Single-Trajectory Chi-Square Robust Q-Learning With Linear Function Approximation

    Oct 2, 2025Saptarshi Mandal, Yashaswini Murthy, R. SrikantQ-LearningModel-Free Reinforcement Learning

  32. Beyond Slater's Condition in Online CMDPs with Stochastic and Adversarial Constraints

    Sep 24, 2025Francesco Emanuele Stradi, Eleonora Fidelia Chiefari, Matteo Castiglioni +2Markov Decision ProcessesO(T^Β)$ Simultaneous Regret

  33. Learning Robust Penetration Testing Policies under Partial Observability: A systematic evaluation

    Sep 24, 2025Raphael Simon, Pieter Libin, Wim MeesPartially Observable Markov Decision ProcessPenetration Testing

  34. Sequential Cohort Selection under Uncertainty

    Aug 22, 2025Hortence Yiepnou, Christos DimitrakakisOptimal PoliciesExpected Utility

  35. Distributionally Robust Markov Games with Average Reward

    Aug 5, 2025Zachary Roch, Yue WangZero--Sum Differential GameMarkov Decision Processes

  36. Learning The Minimum Action Distance

    Jun 10, 2025Lorenzo Steccanella, Joshua B. Evans, Özgür Şimşek +1Markov Decision ProcessesGoal-Conditioned Reinforcement Learning

  37. Shared Modular Recurrence in Contextual MDPs for Universal Morphology Control

    Jun 10, 2025Laurens Engwegen, Max Weltevrede, Caroline Horsch +2Scalable Robot LearningIterative Reinforcement Learning

  38. Continuous Policy and Value Iteration for Stochastic Control Problems and Its Convergence

    Jun 9, 2025Qi Feng, Gu WangStochastic Optimal ControlValue Functions

  39. Efficient Q-Learning and Actor-Critic Methods for Robust Average-Reward Reinforcement Learning

    Jun 8, 2025Yang Xu, Swetha Ganesh, Vaneet AggarwalQ-LearningSoft Actor-Critic

  40. SafeOR-Gym: A Benchmark Suite for Safe Reinforcement Learning Algorithms on Practical Operations Research Problems

    Jun 2, 2025Asha Ramanujam, Adam Elyoumi, Hao Chen +5Safety ConstraintsDeep Reinforcement Learning

  41. Model-Free Robust Average-Reward Reinforcement Learning with Sample Complexity Analysis

    May 18, 2025Zachary Roch, George Atia, Yue WangModel-Free Reinforcement LearningOptimal Policies

  42. Adaptive Resolving Methods for Markov Decision Processes with Function Approximations

    May 17, 2025Jiashuo Jiang, Yinyu Ye, Yiming ZongMarkov Decision ProcessesOptimal Policies

  43. Reinforcement Learning in Switching Non-Stationary Markov Decision Processes: Algorithms and Convergence Analysis

    Mar 24, 2025Mohsen Amiri, Sindri MagnússonMarkov Decision ProcessesConvergence Analysis

  44. Evolutionary Guided Decoding: Iterative Value Refinement for LLMs

    Mar 4, 2025Zhenhua Liu, Lijun Li, Ruizhe Chen +5Large Language Model AlignmentDiffusion Language Models

  45. Statistical Inference for Policy Evaluation with Temporal Difference Learning

    Oct 21, 2024Weichen Wu, Gen Li, Yuting Wei +1Temporal DifferenceValue Functions

  46. Training on Irrelevant States Implies Data Augmentation: Generalization in Contextual MDPs

    Oct 4, 2024Max Weltevrede, Caroline Horsch, Matthijs T. J. Spaan +1Efficient ExplorationMarkov Decision Processes

  47. Bridging Rested and Restless Bandits with Graph-Triggering: Rising and Rotting

    Sep 9, 2024Gianmarco Genalti, Marco Mussi, Nicola Gatti +3Multi-Armed BanditsBandits

  48. Thompson Sampling for Infinite-Horizon Discounted Decision Processes

    May 14, 2024Daniel Adelman, Cagla Keceli, Alba V. Olivares-NadalThompson SamplingMarkov Decision Processes

  49. Neural Dynamic Data Valuation via Stochastic State-Adjoint Trajectories

    Apr 30, 2024Zhangyong Liang, Ji Zhang, Huanhuan GaoCoalition FormationValue

  50. Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms

    Apr 4, 2024Miao Lu, Han Zhong, Tong Zhang +1Markov Decision ProcessesDistributional Learning

  51. Bridging the Gap between Newton-Raphson Method and Regularized Policy Iteration

    Oct 11, 2023Zeyang Li, Chuxiong Hu, Yunan Wang +4Entropy Regularized Reinforcement LearningPolicy Gradient

  52. Reinforcement Federated Learning Method Based on Adaptive OPTICS Clustering

    Jun 22, 2023Tianyu Zhao, Junping Du, Yingxia Shao +1Federated LearningDistributional Learning

  53. Unfair Utilities and First Steps Towards Improving Them

    Jun 1, 2023Frederik Hytting Jørgensen, Sebastian Weichwald, Jonas PetersFairness ConstraintsExpected Utility

  54. Incentives to Offer Algorithmic Recourse

    Jan 27, 2023Matthew Olckers, Toby WalshRejectionIncentives

  55. Policy design in experiments with unknown interference

    Nov 16, 2020Davide Viviano, Jess RudderBayesian Experimental DesignWelfare

  56. Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning

    Date pendingZikang Shan, Han Zhong, Liwei Wang +1Critic-Free Reinforcement LearningSoft Actor-Critic

  57. Independent Learning of Nash Equilibria in Partially Observable Markov Potential Games with Decoupled Dynamics

    Date pendingPhilip Jordan, Maryam KamgarpourNash EquilibriumPartially Observable Markov Decision Process

  58. Optimization-Based Robust Permissive Synthesis for Interval MDPs

    Date pendingKhang Vo Huynh, David Parker, Lu FengMarkov Decision ProcessesConstraint-Aware Synthesis

  59. Safe Learning Under Irreversible Dynamics via Asking for Help

    Date pendingBenjamin Plaut, Juan Liévano-Karim, Hanlin Zhu +1Markov Decision ProcessesNear-Optimal Regret Guarantees