Markov Decision Processes

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Optimal PoliciesValue FunctionsBellman EquationPartially Observable Markov Decision Process

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Period ending 2026-09-21

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174 papers

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  1. Entropy Objectives in Markov Decision Processes

    Jun 19, 2026S. Akshay, Raghav Goyal, Aditya Neeraje +1Markov Decision ProcessesObjectives

  2. Off-Policy Evaluation for Missingness-Aware Policies in MDPs with Rewards Missing Not at Random

    Jun 18, 2026Ziheng Wei, Annie Qu, Rui MiaoOff-Policy EvaluationMissing Data

  3. VOiLA: Vectorized Online Planning with Learned Diffusion Models for POMDP Agents

    Jun 18, 2026Marcus Hoerger, Rishikesh Joshi, Rahul Shome +2Partially Observable Markov Decision ProcessDiffusion Planning

  4. Can In-Context Learning Support Intrinsic Curiosity?

    Jun 17, 2026Eric Elmoznino, Sangnie Bhardwaj, Johannes von Oswald +5In-Context LearningEntropy Regularized Reinforcement Learning

  5. Pareto Q-Learning with Reward Machines

    Jun 17, 2026Arnaud Lequen, Clément Legrand-Lixon, Léo SaulièresQ-LearningConstrained Reinforcement Learning

  6. Maturing Markov Decision Processes: Decision Making under Increasing Information and Shrinking Action Sets

    Jun 17, 2026Jiaxi Liu, Aiping Yang, Yuhang Yang +4Markov Decision ProcessesMulti-Objective Policy Optimization

  7. When Should a Robot Replan? Regret-Guided Update Scheduling in Time-Varying MDPs

    Jun 15, 2026Negin Musavi, Gokul Puthumanaillam, Ruben Hernandez +2Dynamic ReplanningMarkov Decision Processes

  8. Learning Policy from a Single Trajectory in Average-Reward Markov Decision Process

    Jun 15, 2026Jongmin Lee, Ernest K. Ryu, Vaneet AggarwalMarkov Decision ProcessesModel-Free Reinforcement Learning

  9. PO-PDDL: Learning Symbolic POMDPs from Visual Demonstrations for Robot Planning Under Uncertainty

    Jun 14, 2026Wenjing Tang, Xuanjin Jin, Yuan Liu +3Partially Observable Markov Decision ProcessBelief Space

  10. Lyapunov-Based Sample Complexity Analysis for Weakly-Coupled MDPs

    Jun 12, 2026Tianhao Wu, Matthew Zurek, Weina Wang +1Markov Decision ProcessesSample Complexity

  11. Utility-Constrained Policy Optimization

    Jun 12, 2026Mehrdad Moghimi, Bernardo Avila PiresConstrained Reinforcement LearningSafety Constraints

  12. Bellman-Taylor Score Decoding for Markov Decision Processes with State-Dependent Feasible Action Sets

    Jun 9, 2026Yi Chen, Rushuai Yang, Qiang Chen +2Markov Decision ProcessesBellman Equation

  13. Seeing Before Colliding: Anticipatory Safe RL with Frozen Vision-Language Models

    Jun 9, 2026Samuel Tetteh, Cody FlemingSafety ConstraintsConstrained Reinforcement Learning

  14. Reformulate LLM Reinforcement Learning for Efficient Training under Black-box Discrepancy

    Jun 7, 2026Jiashun Liu, Runze Liu, Xu Wan +3Training-Inference MismatchReinforcement Learning Post-Training

  15. Bayesian learning for the stochastic shortest path problem

    Jun 3, 2026Chon Wai Ho, Sumeetpal S. Singh, Jiaqi GuoMarkov Decision ProcessesBayesian

  16. Policy Gradient for Continuous-Time Robust Markov Decision Processes

    Jun 3, 2026Tanya Veeravalli, David M. Bossens, Atsushi NitandaMarkov Decision ProcessesPolicy Gradient

  17. A Goal-Set Characterization of Task Composition in the Boolean Task Algebra

    Jun 2, 2026Eduardo Terrés-Caballero, Herke van HoofValue FunctionsGoal-Conditioned Reinforcement Learning

  18. Task-Induced Representational Invariances Depend on Learning Objective in Deep RL

    Jun 1, 2026Manu Srinath Halvagal, Sebastian Lee, SueYeon ChungDeep Reinforcement LearningRepresentation Learning

  19. Interaction-Limited Safe Continuous-Time RL for Dynamical Medical Treatment

    May 31, 2026Xun Shen, Yuepeng Wang, Akifumi Wachi +13Safety ConstraintsTreatment

  20. Prospect-Theory Behavior from Bellman Optimality in MDPs with Catastrophic States

    May 31, 2026Yujiao ChenMarkov Decision ProcessesBellman Equation

  21. Topology-Aware State Abstraction with Tangle Cores for Markov Decision Processes

    May 29, 2026Ibne Farabi Shihab, Sanjeda Akter, Anuj SharmaMarkov Decision ProcessesTopological Data Analysis

  22. Reinforcement Learning with Pairwise Preferences in Long-Term Decision Problems

    May 29, 2026Jonathan Colaço Carr, Prakash Panangaden, Doina Precup +1Markov Decision ProcessesOptimal Policies

  23. Robust Shielding for Safe Reinforcement Learning

    May 29, 2026Edwin Hamel-De le Court, Thom Badings, Alessandro Abate +2ShieldingMarkov Decision Processes

  24. Value Functions as Supermartingale Certificates

    May 29, 2026Alessandro Abate, Daniel Contro, Mirco Giacobbe +2Value FunctionsReinforcement Learning With Verifiable Reward

  25. The Challenges of Using Reinforcement Learning for Controlling Industrial Energy Systems

    May 29, 2026Tobias Lademann, Théo Vincent, Jan Peters +1Iterative Reinforcement LearningMarkov Decision Processes

  26. PatchWorld: Gradient-Free Optimization of Executable World Models

    May 29, 2026Jiaxin Bai, Yue Guo, Yifei Dong +13World ModelsMarkov Decision Processes

  27. Variance-Adaptive Optimal Algorithm for Reinforcement Learning with Multinomial Logit Function Approximation

    May 27, 2026Wonyoung Kim, Min-Hwan Oh, Garud Iyengar +1Near-Optimal Regret GuaranteesMarkov Decision Processes

  28. Commit to the Bit: Reactive Reinforcement Learning Done Right

    May 27, 2026Onno Eberhard, Claire Vernade, Michael MuehlebachQ-LearningMarkov Decision Processes

  29. Transferable Reinforcement Learning via Probabilistic Latent Embeddings and Dynamic Policy Adaptation for Sim-to-Real Deployment

    May 26, 2026Gengyue Han, Yiheng FengZero-Shot Sim-To-Real TransferSim-To-Real Gap

  30. Global linear convergence of entropy-regularized softmax policy gradient beyond tabular MDPs

    May 24, 2026Ziyue Chen, David Šiška, Lukasz SzpruchPolicy GradientEntropy-Regularized Equilibrium Selection

  31. Evolving Robustness--Exploration Trade-off in Online Reinforcement Learning via Quantile Bayesian Risk MDPs

    May 23, 2026Meichen Song, Yuhao Wang, Enlu ZhouMarkov Decision ProcessesBayesian

  32. Learning Kernel-Based MDPs from Episodic Preferential Feedback

    May 22, 2026Nikola Pavlovic, Sattar Vakili, Qing ZhaoReinforcement Learning From Human FeedbackEntropy Regularized Reinforcement Learning

  33. Reflex: Reinforcement Learning with Reflection Symmetry Exploitation in State-Based Continuous Control

    May 22, 2026Shuai Zhen, Yifan Zhang, Yuling Wang +1Markov Decision ProcessesReflections

  34. Abstraction for Offline Goal-Conditioned Reinforcement Learning

    May 21, 2026Clarisse Wibault, Alexander Goldie, Antonio Villares +2Goal-Conditioned Reinforcement LearningMarkov Decision Processes

  35. A note on convergence of Wasserstein policy optimization

    May 21, 2026David Šiška, Yufei ZhangWasserstein Gradient FlowsMarkov Decision Processes

  36. Scaling Observation-aware Planning in Uncertain Domains

    May 21, 2026Adrian Zvizdenco, Arthur Conrado Veiga Bosquetti, Alberto Lluch Lafuente +1Partially Observable Markov Decision ProcessPartial Observability

  37. On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents

    May 20, 2026Oliver Mortensen, Mohammad Sadegh TalebiValue FunctionsMarkov Decision Processes

  38. ReversedQ: Opportunities for Faster Q-Learning in Episodic Online Reinforcement Learning

    May 20, 2026Sofia R. Miskala-Dinc, Aviva PrinsQ-LearningModel-Free Reinforcement Learning

  39. Minimax Optimal Variance-Aware Regret Bounds for Multinomial Logistic MDPs

    May 19, 2026Pierre Boudart, Pierre Gaillard, Alessandro RudiNear-Optimal Regret GuaranteesMarkov Decision Processes

  40. Learning to Hand Off: Provably Convergent Workflow Learning under Interface Constraints

    May 18, 2026Jiayu Li, Enpei Zhang, Dawei Zhou +2Q-LearningMulti-Agent Workflows

  41. MATE: Solving Contextual Markov Decision Processes with Memory of Accumulated Transition Embeddings

    May 17, 2026Himchan Hwang, Hyeokju Jeong, Gene Chung +3Markov Decision ProcessesMarkov

  42. Second-Order Actor-Critic Methods for Discounted MDPs via Policy Hessian Decomposition

    May 14, 2026Sanjeev Manivannan, Shuban VSoft Actor-CriticMarkov Decision Processes

  43. Synthesizing POMDP Policies: Sampling Meets Model-checking via Learning

    May 14, 2026Debraj Chakraborty, Anirban Majumdar, Prince Mathew +2Partially Observable Markov Decision ProcessMarkov Decision Processes

  44. Dynamic Latent Routing

    May 14, 2026Fangyuan Yu, Xin Su, Amir AbdullahEfficient Latent ReasoningMarkov Decision Processes

  45. Action-Conditioned Risk Gating for Safety-Critical Control under Partial Observability

    May 14, 2026Yushen Liu, Yin-Jen Chen, Ziyi Chen +4Belief SpaceSafety-Critical Scenarios

  46. Adaptive mine planning under geological uncertainty: A POMDP framework for sequential decision-making

    May 13, 2026Hamza Khalifi, Jef Caers, Yassine Taha +2Partially Observable Markov Decision ProcessMarkov Decision Processes

  47. Differentiable Learning of Lifted Action Schemas for Classical Planning

    May 13, 2026Jonas Reiter, Jakob Elias Gebler, Hector GeffnerClassical PlanningPlanning Methods

  48. State-Centric Decision Process

    May 12, 2026Sungheon Jeong, Ryozo Masukawa, Sanggeon Yun +2Markov Decision ProcessesAgent Decisions

  49. Ensuring Logic in the Fog: Sound POMDP Synthesis with LTL Objectives

    May 12, 2026Can Zhou, Yulong Gao, Pian YuLinear Temporal LogicsPartially Observable Markov Decision Process

  50. Missingness-MDPs: Bridging the Theory of Missing Data and POMDPs

    May 12, 2026Joshua Wendland, Markel Zubia, Roman Andriushchenko +6Partially Observable Markov Decision ProcessMissing Data

  51. Split the Differences, Pool the Rest: Provably Efficient Multi-Objective Imitation

    May 12, 2026Ziyad Sheebaelhamd, Luca Viano, Volkan Cevher +1Imitation LearningBehavior Cloning

  52. Federated Client Selection under Partial Visibility: A POMDP Approach with Spatio-Temporal Attention

    May 12, 2026Qijun Hou, Yuchen Shi, Pingyi Fan +1Federated LearningPartially Observable Markov Decision Process

  53. Augmented Lagrangian Method for Last-Iterate Convergence for Constrained MDPs

    May 12, 2026Michael Lu, Max Qiushi Lin, Mo Chen +1Markov Decision ProcessesExponential Horizon Dependence

  54. Learning Weakly Communicating Average-Reward CMDPs: Strong Duality and Improved Regret

    May 12, 2026Kihyun Yu, Beomhan Baek, Dabeen LeeMarkov Decision ProcessesLinear Regret

  55. Primal-Dual Policy Optimization for Linear CMDPs with Adversarial Losses

    May 12, 2026Kihyun Yu, Seoungbin Bae, Dabeen LeePrimal-Dual MethodsMarkov Decision Processes

  56. Shields to Guarantee Probabilistic Safety in MDPs

    May 11, 2026Linus Heck, Filip Macák, Roman Andriushchenko +2ShieldingSafety Constraints

  57. Policy Gradient Methods for Non-Markovian Reinforcement Learning

    May 11, 2026Avik Kar, Siddharth Chandak, Rahul Singh +4Markov Decision ProcessesPolicy Gradient

  58. Switching-Geometry Analysis of Deflated Q-Value Iteration

    May 11, 2026Donghwan LeeQ-LearningConvergence Analysis

  59. Attribution-based Explanations for Markov Decision Processes

    May 10, 2026Paul Kobialka, Andrea Pferscher, Francesco Leofante +3Markov Decision ProcessesArtificial Intelligence Models

  60. Minimizing Worst-Case Weighted Latency for Multi-Robot Persistent Monitoring: Theory and RL-Based Solutions

    May 10, 2026Weizhen Wang, Ziheng Wang, Jianping He +2Multi-Robot SystemsConstrained Reinforcement Learning