Markov Decision Processes

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Period ending 2026-09-21

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  1. A Decentralized Partially Observable Team Decision Methodology with Delayed Information Sharing

    Sep 22, 2026Xiaoxing Ren, Thomas Parisini, Andreas A. MalikopoulosPartially Observable Markov Decision ProcessDecentralization

  2. Reinforcement Learning under State and Outcome Uncertainty: A Foundational Distributional Perspective

    Sep 21, 2026Larry Preuett, Qiuyi Zhang, Muhammad Aurangzeb AhmadPartially Observable Markov Decision Process

  3. Model-based Bootstrap for Offline Policy Evaluation in Tabular Reinforcement Learning

    Sep 17, 2026Weiwei Wang, Yuqiang Li, Xianyi Wu +1Off-Policy EvaluationMultiplier Bootstrap

  4. Graph-Based Stochastic Power-UCT: Monte-Carlo Graph Search with Power Mean Estimation

    Sep 17, 2026Tung Tran, Viet Bao Mai, Hoang Ta +1Monte Carlo Tree SearchMarkov Decision Processes

  5. Stable Policy Learning

    Sep 16, 2026Harvey Barnhard, Giacomo Opocher, Rahul SinghOptimal PoliciesImportance Sampling

  6. Task-Oriented Active Learning of Residual Dynamics for Model Predictive Path Integral Control

    Sep 16, 2026Nobuaki Aoki, Hojin Lee, Stefan Sosnowski +1Model Predictive Path IntegralActive Learning

  7. Exponential Hardness of Off-Policy Evaluation under History-Dependent Logging

    Sep 16, 2026Pranaya JajooOff-Policy EvaluationPartially Observable Markov Decision Process

  8. Social Laws for Multi-agent Coordination in Stochastic Environments

    Sep 16, 2026Rolando Fernandez, Caleb Probine, Tyler Lee +5Multi-Agent CoordinationMulti-Agent Systems

  9. A Convergence Framework for Deep VV-Learning: Error Propagation and Sharp Action-Gap Bounds

    Sep 16, 2026Yury KolomeytsevQ-LearningBellman Equation

  10. A Geometric Theory of Decision Boundaries in Structured Markov Decision Processes

    Sep 16, 2026Fredy PokouMarkov Decision ProcessesBoundaries

  11. Symmetric solution of the Bellman optimality equation for repeated harmony game

    Sep 14, 2026Hisato KomatsuBellman EquationSymmetry

  12. Bellman Policy Optimization

    Sep 14, 2026Zhuoqing Song, Haotian Xu, Xikun Zhang +1Reinforcement Learning With Verifiable RewardMulti-Objective Policy Optimization

  13. Strong and Compact Policies for Submodular Markov Decision Processes via LP-Based Submodular Orienteering

    Sep 14, 2026Lars Rohwedder, Rico ZenklusenMarkov Decision ProcessesSubmodular Maximization

  14. Evaluation Metrics for Safe Reinforcement Learning

    Sep 14, 2026Lindsay Spoor, Aske Plaat, Thomas MoerlandSafety EvaluationJoint Reinforcement Learning

  15. Supermartingale Certificates for Parametric MDPs

    Sep 14, 2026Kaushik Mallik, \DHorj̣e ŽikelićMarkov Decision ProcessesConformal Test Martingales

  16. Adaptive Agent Design

    Sep 14, 2026Raj Kiriti Velicheti, Subhonmesh Bose, Tamer BaşarQ-LearningMarkov Decision Processes

  17. Certified Safety Curation: Distribution-Free Guarantees for Safe Offline Reinforcement Learning

    Sep 14, 2026Adam Haroon, Cody FlemingOffline Reinforcement LearningSafety Constraints

  18. Learning to Solve Stochastic Controls with Unknown Drifts and Running Rewards: Theory, Algorithms and Convergence

    Sep 14, 2026Jin Ma, Gaozhan Wang, Jianfeng Zhang +1Stochastic Optimal ControlValue Functions

  19. A Bellman Optimality Equation for Plasticity

    Sep 11, 2026Jeremy Lucas, Doina PrecupPlasticityBellman Equation

  20. DIA: Denoising Intermediate Advantage for Diffusion Policy Optimization

    Sep 10, 2026Arjun Sohal, Yuchi Zhao, Miroslav Bogdanovic +1Diffusion PoliciesBehavior Cloning

  21. Support Discovery With Iteratively Reweighted Least Squares for Fixed-Charge Network Flow

    Sep 10, 2026Sindura Saraswathi, Christian KümmerleMixed-Integer ProgrammingLeast Squares

  22. Learning Intrusion Response Strategies for OT Systems

    Sep 9, 2026Duc Huy Le, Rolf StadlerIntrusion DetectionIncident Response

  23. Belief-State Engine: Augmenting LLMs for Principled Planning Under Partial Observability

    Sep 9, 2026Arnab Chattopadhayay, Debdipta HalderPartially Observable Markov Decision ProcessLatent States

  24. Optimal Value Inference for Reinforcement Learning

    Sep 9, 2026Nan Lu, Ethan Lee, James M. Robins +2Bellman Equation

  25. BRACE: Anchored Bellman-Residual Correction for Stale Critics in Asynchronous RL

    Sep 9, 2026Guanqun Zhao, Zijun Xie, Binbin Zheng +3Gradient StalenessCorrection

  26. The Surprising Effectiveness of Approximate Value Iteration in Self-Play

    Sep 8, 2026Raphael Boige, Amine Boumaza, Bruno ScherrerSelf-PlayMonte Carlo Tree Search

  27. CAST: Alternating State-Value Targets and Expanded Policy Gradients for Model-Based Reinforcement Learning

    Sep 8, 2026Pietro Noah Crestaz, Mohamed Yassine Kabouri, Nicolas Mansard +1Value FunctionsSoft Actor-Critic

  28. Mini-Batch Risk-Averse Deep Q-Learning: A Robot Navigation Case Study

    Sep 7, 2026Aayush Patel, Andrzej RuszczyńskiMarkov Decision ProcessesSocial Robot Navigation

  29. Conditional Timed Partial Orders: An Expressive and Interpretable Framework for Robot Task Specification and Planning

    Sep 7, 2026Sebastian Escobar, Morteza LahijanianPartially Observable Markov Decision ProcessPlanning Methods

  30. Temporal-Causal Inference for Reinforcement Learning via Automata Learning

    Sep 7, 2026Jan Corazza, Daniil Kaminskyi, Simon Lutz +4Entropy Regularized Reinforcement LearningMarkov Decision Processes

  31. Robust PAC Learning of Concurrent Stochastic Games

    Sep 3, 2026Angel Y. He, David ParkerZero--Sum Differential GameNash Equilibrium

  32. Scalable Rao-Blackwellized Online Planning for High-Dimensional POMDPs

    Sep 1, 2026Jiho Lee, Nisar Ahmed, Kyle Hollins Wray +1Robot PlanningPartially Observable Markov Decision Process

  33. Locally-Guided Actor-Critic: Training a Goal-conditioned Actor with a Subgoal-aware Critic

    Aug 31, 2026Olivier Serris, Stéphane Doncieux, Olivier SigaudGoal-Conditioned Reinforcement LearningGoal-Conditioned Policy

  34. GPAgentBench-2K: Benchmarking Large Language Model Agents in Complex Clinical Action Space

    Aug 31, 2026Boqi Chen, Xudong Liu, Yunke Ao +2Large Language Model AgentsOpti-Agent-Bench

  35. Game-Agnostic Value Functions through Automatic JSON Feature Extraction

    Aug 30, 2026Dien Nguyen, Diego Perez-LiebanaValue FunctionsValue

  36. From Relaxed Indexability to Exact Indexability: A tt-Step Approach for Partially Observable Restless Bandits

    Aug 25, 2026Qizhen Jia, Keqin LiuLinear BanditsOptimal Policies

  37. Fast A/B/n Testing: Exact Multi-Policy Comparison via Tree-Coupled Feedback Sharing

    Aug 13, 2026Yuxiao WenOptimal PoliciesFeedback Learning

  38. Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value

    Aug 13, 2026Akihito SudoValue FunctionsValue

  39. Decentralized Multi-Player Q-Learning in Episodic Markov Decision Processes with Information Asymmetry

    Aug 13, 2026Larissa Xu, King Bi, William ChangQ-LearningMulti-Agent Reinforcement Learning

  40. Towards a Formal Definition of Agent Memory: Basis, Span, Optimality, and the Sequential Memory Problem

    Aug 12, 2026Hongyao TangAgent MemorySubstantial Memory

  41. Threshold Structure of Optimal Policies in Restart POMDPs

    Aug 11, 2026Konstantin Avrachenkov, Alexey Piunovskiy, Yi ZhangPartially Observable Markov Decision ProcessMarkov Decision Processes

  42. Boundary-Seeking Policy Gradient for Safe Reinforcement Learning

    Aug 10, 2026Chenhua Fan, Jiahui Zhu, Yuhang Zhang +1Policy GradientSafety Constraints

  43. Path-dependent Discrete Amortized Inference

    Aug 9, 2026Tiago da Silva, Esmeralda S. Whitammer, Salem LahlouMarkov Decision ProcessesPosterior

  44. Per-Shipment Multi-Agent Reinforcement Learning for Intermodal Freight Routing Under Hurricane Disruption

    Aug 7, 2026Aliza Sharmin, Xudong Wang, Mustafa Can Camur +1Last MileMulti-Agent Reinforcement Learning

  45. The Sample Complexity of Policy Learning with Mu-Resets

    Aug 7, 2026Gene LiOptimal PoliciesOptimal Sample Complexity

  46. Finite Constant Frontiers and Auditable Regret Certificates for Average-Reward Reinforcement Learning

    Aug 7, 2026Ibne Farabi Shihab, Abu Sa-Adat Mohamed Moon-Im Al Ahsan, Md Najmus SwaqeebEntropy Regularized Reinforcement LearningMarkov Decision Processes

  47. CODS: Iterative Bellman-Residual Data Selection for Reusable Offline Reinforcement Learning

    Aug 7, 2026Ibne Farabi Shihab, Sanjeda Akter, Abu Sa-Adat Mohamed Moon-Im Al Ahsan +2Offline Reinforcement LearningBellman Equation

  48. Aftab: A Comprehensive Benchmark of CNN Encoders and Advanced Value Functions in Parallelized Q-Networks

    Aug 7, 2026Taha Shieenavaz, Shabnam Zareshahraki, Loris NanniDeep Q-NetworksDeep Reinforcement Learning

  49. From Optimal Actions to World Models: Identifiability of Transition Kernels in Discounted MDPs

    Aug 7, 2026Neal BatraMarkov Decision ProcessesOptimal Actions

  50. Sub-Quadratic Bisimulation Metrics via Approximate Nearest Neighbors: Coverage-Augmented Guarantees and Computable Two-Sided Certificates

    Aug 7, 2026Ibne Farabi Shihab, Joyanta Jyoti MondalFinite-Sample CertificatesMarkov Decision Processes

  51. Bootstrap-Conditioned Action Selection with Tabular Foundation Models

    Aug 6, 2026Devansh Gupta, Shiv Tavker, Dmitry Efimov +3Linear Contextual BanditsIn-Context Learning

  52. Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions

    Aug 6, 2026Yuepeng Yang, Yuxin Chen, Yuejie ChiMarkov Decision ProcessesOptimal Policies

  53. Online Security Learning in Cooperative Multi-Agent Systems under Hidden Byzantine Attacks

    Aug 6, 2026Ximing Sun, Yue WangByzantine AttacksMulti-Agent Systems

  54. MACRO: Markov Chain Routing of Transformer Layers

    Aug 6, 2026Paweł Batorski, Abtin Pourhadi, Akylgali Aitaza +2Large Language Model RoutingTransformer Layers

  55. Exact Model-Free Policy Iteration for Co-safe LTL Planning

    Aug 5, 2026Zetong Xuan, Yu WangModel-Free Reinforcement LearningLinear Temporal Logics

  56. Optimal Constrained sc-LTL Planning in MDPs via Switching Policies

    Aug 5, 2026Zetong Xuan, Yu WangLinear Temporal LogicsMarkov Decision Processes

  57. Differentiating Through Dual Prices: End-to-End Policy Learning Under Capacity Constraints

    Aug 5, 2026Mohammadsaeed Haghi, Mahdi Salmani, Nima KelidariStochastic DelaysPrices

  58. Adaptive Finite-Budget Training for CVaR Risk-Aware Q-Learning

    Aug 5, 2026Yifan Wu, Junjie Lei, Wenjie HuangConditional-Value-At-RiskQ-Learning

  59. POMDPs for Autonomous Science Exploration

    Aug 4, 2026Daniel Guirguis, Nathan Wallace, Hanna Kurniawati +1Belief SpacePartially Observable Markov Decision Process

  60. Minimax-Optimal Semiparametric Contextual Dynamic Pricing with Multimodal Revenue

    Aug 4, 2026Xueping Gong, Zhuoluo Zhang, Zhaowei Miao +1PricesSemiparametric Framework