Markov Decision Processes

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Period ending 2026-09-21

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  1. Stochastic Linear Bandits with Partially Observed Actions

    Jul 9, 2026Gautam Dasarathy, Vineet Gattani, Lalit JainPartially Observable Markov Decision ProcessPart

  2. SafeExplorer: An Unbiased Policy Gradient for Reinforcement Learning with Recovery Interventions

    Jul 9, 2026Elham Daneshmand, Majid Khadiv, Glen Berseth +1Proximal Policy OptimizationImitation Learning

  3. Offline Nash Solvers Meet Online Tree Search in Multi-Agent Games on Graphs

    Jul 9, 2026Mukesh Kumar, Yue Guan, Panagiotis TsiotrasNash EquilibriumMulti-Agent Path Finding

  4. Statistical Efficiency and Inference of Quantile Distributional Reinforcement Learning

    Jul 9, 2026Zijie Cheng, Yang Peng, Zhihua ZhangQuantile RegressionDistributional Learning

  5. Provably Optimal Learning Algorithms for Assistance Games

    Jul 9, 2026Nivasini Ananthakrishnan, Mark Bedaywi, Michael I. Jordan +2Multi-Agent Reinforcement LearningOptimal Policies

  6. Principled Analysis of Deep Reinforcement Learning Evaluation and Design Paradigms

    Jul 8, 2026Ezgi KorkmazJoint Reinforcement LearningDeep Reinforcement Learning

  7. Mathematical methods of reinforcement learning

    Jul 8, 2026Denis Belomestny, Alexander Gasnikov, Egor Gladin +5Entropy Regularized Reinforcement LearningMarkov Decision Processes

  8. Fitted Occupancy-Ratio Evaluation without Bellman Completeness

    Jul 6, 2026Lars van der Laan, Nathan KallusBellman EquationOffline Reinforcement Learning

  9. Deep Learning for Dynamic Programming with Recursive Utility

    Jul 5, 2026Xianhua Peng, Wu GuoValue FunctionsDeep Learning

  10. CDCP: Conditional Diffusion Model with Contextual Prompts for Multi-task Offline Safe Reinforcement Learning

    Jul 4, 2026Jiayi Guan, Tianle Zhang, Li Shen +8Offline Reinforcement LearningDiscrete Diffusion Model

  11. A Hierarchy of Policy Learning Problems

    Jul 3, 2026Hamsa Bastani, Osbert Bastani, Shihan ChenOptimal PoliciesLinear Regret

  12. Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning

    Jul 3, 2026Jialun Cao, Fernando Acero, David Šiška +1Entropy Regularized Reinforcement LearningKullback-Leibler Regularization

  13. ACPO: Adaptive Credit Policy Optimization via Fine-Grained Surrogate Entropy

    Jul 3, 2026Zijun Xie, Yuyang You, Yongzhi Li +6Credit AssignmentEntropy-Regularized Equilibrium Selection

  14. Generalization in offline RL: The structure is more important than the amount of pessimism

    Jul 2, 2026Max Weltevrede, Matthijs T. J. Spaan, Wendelin BöhmerOffline Reinforcement LearningPessimism

  15. Tight Lower Bounds for the Multi-Secretary Problem via Bellman Certificates

    Jul 2, 2026Jiawei ZhangLinear RegretLower Bounds

  16. Learning the Supports for Categorical Critic in Reinforcement Learning

    Jul 2, 2026Jen-Yen Chang, Takayuki Osa, Tatsuya HaradaSoft Actor-CriticValue Functions

  17. Policy Optimization Achieves Data-Dependent Regret Bounds in MDPs with Unknown Transitions

    Jun 30, 2026Mingyi Li, Taira Tsuchiya, Kenji YamanishiMarkov Decision ProcessesTransitions

  18. ShardNet: Training Neural Controllers with Hard, Non-Convex Constraints

    Jun 29, 2026Long Kiu Chung, Shreyas KousikNeural ControlSafety Constraints

  19. Sample-Efficient Learning of Probabilistic Causes for Reachability in Markov Decision Processes with Probabilistic Guarantees

    Jun 29, 2026Ryohei Oura, Georgios Fainekos, Hideki Okamoto +1Markov Decision ProcessesReachability

  20. Priced Motion Through Optimal Faces: A Normal-Fan Geometry for Non-Stationary Adversarial MDPs

    Jun 27, 2026Kai HidajatOptimal PoliciesMarkov Decision Processes

  21. Regularized Reward-Punishment Reinforcement Learning

    Jun 26, 2026Jiexin Wang, Eiji UchibeDeep Q-NetworksBellman Equation

  22. Learning in Markovian bandits with non-observable states and constrained decision epochs

    Jun 25, 2026Thomas Hira, Victor Boone, Urtzi Ayesta +1O(T^Β)$ Simultaneous RegretMarkov Decision Processes

  23. Asymptotically Optimal Learning for Parametric Prophet Inequalities

    Jun 25, 2026Jung-hun Kim, Anna Grebennikova, Vianney PerchetConcentration InequalitiesOptimal Policies

  24. Mean-Field PhiBE: Continuous-Time Mean-Field Reinforcement Learning from Discrete-Time Data

    Jun 25, 2026Erhan Bayraktar, Martin Hernandez, Qinxin Yan +1Model-Free Reinforcement LearningStochastic Optimal Control

  25. Deterministic Pareto-Optimal Policy Synthesis for Multi-Objective Reinforcement Learning

    Jun 24, 2026Aniruddha Joshi, Niklas Lauffer, Sanjit SeshiaConstrained Reinforcement LearningOptimal Policies

  26. Confidence Sequences for Online Statistical Model Checking of Markov Decision Processes

    Jun 24, 2026Konstantin Kueffner, Tobias Meggendorfer, Maximilian Weininger +1Markov Decision ProcessesConfidence Intervals

  27. Low-Complexity Policy Tessellations in Structured Markov Decision Processes

    Jun 24, 2026Fredy PokouMarkov Decision ProcessesOptimal Policies

  28. Implementation of reinforcement learning in chemical reaction networks: application to phototaxis as curiosity-driven exploration

    Jun 24, 2026Ruyi Tang, Grégoire Sergeant-Perthuis, David ColliauxPartially Observable Markov Decision ProcessReaction

  29. Minimax PAC Bounds for Learning in Exogenous Contextual MDPs

    Jun 23, 2026Corentin Pla, Hugo Richard, Marc Abeille +1Markov Decision ProcessesMinimax

  30. World Value Models for Robotic Manipulation

    Jun 23, 2026Zhihao Wang, Jianxiong Li, Yu Cui +4Value Functions

  31. Solving Markov Decision Processes with Future Information via MPC

    Jun 23, 2026Shambhuraj Sawant, Akhil S Anand, Dirk Reinhardt +1Model Predictive ControlMarkov Decision Processes

  32. Beyond Monotonic Progress: Retry-Supervised Value Learning for Robot Imitation

    Jun 23, 2026Xinyao Qin, Junjie Lu, Kaixin Wang +7Imitation LearningImitation

  33. Welfarist Control Design -- How to fulfill the societal mandate in multi-agent control?

    Jun 22, 2026Sophie Hall, Kai Zhang, Ilia Shilov +2Feedback LinearizationSociotechnical Systems

  34. Hessian-augmented Supervised Learning for Hamilton-Jacobi-Bellman PDEs

    Jun 22, 2026Matías Gómez-Aedo, Behzad Azmi, Yuyang Huang +2Optimal ControlHamilton-Jacobi Reachability

  35. Stationary Robust Mean-Field Games under Model Mismatches

    Jun 21, 2026Yue WangMulti-Agent Reinforcement LearningZero--Sum Differential Game

  36. PolicyTrim: Boosting Intrinsic Policy Efficiency of Vision-Language-Action Models

    Jun 21, 2026Xianghui Wang, Feng Chen, Wenbo Zhang +4Vision-Language-Action ModelsInference Latency

  37. Fed-CausalDiff: Decoupled Synchronization for Federated Do-Simulation and Policy Evaluation

    Jun 21, 2026Pengfei Li, Mohammad KhalilFederated LearningDiffusion Policies

  38. REBA: A Revealed Belief Automaton Framework for Online Planning in Continuous POMDPs

    Jun 20, 2026Xiangwei Chen, Lingling Fang, Andreas Holzinger +1Partially Observable Markov Decision ProcessBelief

  39. Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning

    Jun 20, 2026Zhao Yang, Yuxuan Jiang, Ting-Chih Chen +18Deep Reinforcement LearningOff-Policy Evaluation

  40. Entropy Objectives in Markov Decision Processes

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

  41. A Transport-Based Geometry of Belief-Cost

    Jun 19, 2026Laurent CaraffaOptimal TransportInference Cost

  42. Inverting the Bellman Equation: From QQ-Values to World Models

    Jun 19, 2026Alistair Letcher, Mattie Fellows, Alexander D. Goldie +3Model-Free Reinforcement LearningGoal-Conditioned Reinforcement Learning

  43. Robust QQ-learning for mean-field control under Wasserstein uncertainty in common noise

    Jun 18, 2026Mathieu Laurière, Ariel Neufeld, Kyunghyun ParkQ-LearningStochastic Optimal Control

  44. Mobile Target Search with Imperfect Perception: A Partially Observable Stochastic Game Theoretical Approach

    Jun 18, 2026Hanzheng Zhang, Shu Liang, Shuyu LiuZero--Sum Differential GamePartially Observable Markov Decision Process

  45. 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

  46. VIMPO: Value-Implicit Policy Optimization for LLMs

    Jun 18, 2026Zhewei Kang, Aosong Feng, Sergey Levine +2Reinforcement Learning With Verifiable RewardValue Functions

  47. 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

  48. Can In-Context Learning Support Intrinsic Curiosity?

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

  49. Pareto Q-Learning with Reward Machines

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

  50. 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

  51. Optimizing Lithium Production Decisions under Geological, Demand, and Pricing Uncertainties: A POMDP Framework for Multi-Objective Decision Making

    Jun 17, 2026Anna C. Edmonds, Mansur M. Arief, Robert J. Moss +2Partially Observable Markov Decision ProcessLithium-Ion Batteries

  52. Sequential Hiring of Contingent Workers Through Learning-Based Optimization

    Jun 16, 2026Chris Lee, Xiuli Chao, Izak DuenyasStochastic DelaysOptimal Bandit Algorithms

  53. A Diffusion Approximation for Temporal-Difference Learning with Linear Features under Markovian Noise

    Jun 16, 2026M. Forzo, E. Monzio Compagnoni, A. Russo +1Temporal DifferenceStochastic Approximation

  54. Learning Fair Pareto-Optimal Policies in Multi-Objective Reinforcement Learning

    Jun 16, 2026Umer Siddique, Peilang Li, Yongcan CaoConstrained Reinforcement LearningOptimal Policies

  55. 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

  56. Deep Q-Learning on Hölder Spaces

    Jun 15, 2026Qian QiQ-LearningDeep Q-Networks

  57. Maximum Entropy Inverse Reinforcement Learning for Mean-Field Games with Average Reward

    Jun 15, 2026Şevket Kaan Alkır, Naci Saldı, Berkay Anahtarcı +1Entropy Regularized Reinforcement LearningBellman Equation

  58. 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

  59. Towards Pareto-Optimal Tool-Integrated Agents with Pareto Ranking Policy Optimization

    Jun 15, 2026Junyi Li, Xiaowei Qian, Yingyi Zhang +6Multi-Turn Tool-Use AgentValue Alignment

  60. Orchestrated Reality: From Role-Play to Living, Playable Game Worlds -- LLM-Driven World Simulation as a Parameterized-Action POMDP

    Jun 14, 2026Yuhang Huang, Chenmiao Li, Chaowei FangRole-Playing AgentsReal-World Environments