Optimal Policies

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4 papers in the last 28 days · 0.1% of indexed attention

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Period ending 2026-09-21

2 new papers

A weekly snapshot of new work published in Optimal Policies.

Period ending 2026-09-14

1 new paper

A weekly snapshot of new work published in Optimal Policies.

105 papers

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Stable Policy Learning
Sep 16, 2026Harvey Barnhard, Giacomo Opocher, Rahul SinghOptimal Policies Importance Sampling
Social Laws for Multi-agent Coordination in Stochastic Environments
Sep 16, 2026Rolando Fernandez, Caleb Probine, Tyler Lee +5Multi-Agent Coordination Multi-Agent Systems
Robust PAC Learning of Concurrent Stochastic Games
Sep 3, 2026Angel Y. He, David ParkerZero--Sum Differential Game Nash Equilibrium
From Relaxed Indexability to Exact Indexability: A $t$ -Step Approach for Partially Observable Restless Bandits
Aug 25, 2026Qizhen Jia, Keqin LiuLinear Bandits Optimal Policies
Fast A/B/n Testing: Exact Multi-Policy Comparison via Tree-Coupled Feedback Sharing
Aug 13, 2026Yuxiao WenOptimal Policies Feedback Learning
Threshold Structure of Optimal Policies in Restart POMDPs
Aug 11, 2026Konstantin Avrachenkov, Alexey Piunovskiy, Yi ZhangPartially Observable Markov Decision Process Markov Decision Processes
The Sample Complexity of Policy Learning with Mu-Resets
Aug 7, 2026Gene LiOptimal Policies Optimal Sample Complexity
Bootstrap-Conditioned Action Selection with Tabular Foundation Models
Aug 6, 2026Devansh Gupta, Shiv Tavker, Dmitry Efimov +3Linear Contextual Bandits In-Context Learning
Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions
Aug 6, 2026Yuepeng Yang, Yuxin Chen, Yuejie ChiMarkov Decision Processes Optimal Policies
Differentiating Through Dual Prices: End-to-End Policy Learning Under Capacity Constraints
Aug 5, 2026Mohammadsaeed Haghi, Mahdi Salmani, Nima KelidariStochastic Delays Prices
Minimax-Optimal Semiparametric Contextual Dynamic Pricing with Multimodal Revenue
Aug 4, 2026Xueping Gong, Zhuoluo Zhang, Zhaowei Miao +1Prices Semiparametric Framework
Improved Quantum Algorithms for Reinforcement Learning Under a Generative Model
Aug 3, 2026Joao F. DoriguelloQ-Learning Quantum Advantage
402Pilot: An x402 Decision Layer for Autonomous Agent Micropayments
Aug 2, 2026Yin Li, Yanbo He, Boo-Ho Yang +5Payment Networks Agent Decisions
Learning Not to Optimize: Physics-Informed Action-Space Reshaping for Intent-Based Network Control
Aug 2, 2026Zuyuan Zhang, Vaneet Aggarwal, Tian LanOptimal Policies Optical Networks
A Unified Algorithmic Framework for Hybrid Reinforcement Learning in Tabular MDPs with Shifted Transition Dynamics
Jul 28, 2026Zheshun Wu, Renjie Zheng, Jinhang Zuo +2Offline Reinforcement Learning Markov Decision Processes
Smooth Learning with Hard Constraints via Legendre-Regularized Policies
Jul 27, 2026Zikun Lin, Rui Chen, Yijie WangOptimal Policies Regularization Techniques
Outcome-Fair Restless Multi-Armed Bandits for Stochastic Deadline Scheduling
Jul 26, 2026Shakti Sharma, Rahul MeshramOptimal Scheduling Linear Bandits
Trajectory-Regularized Stochastic Optimal Control via KL Divergence
Jul 24, 2026Mintae Kim, Koushil SreenathStochastic Optimal Control Kullback-Leibler Regularization
Robust Asynchronous Q-Learning under Reward and State Corruption via Batching
Jul 23, 2026Sreejeet Maity, Aritra MitraQ-Learning Adversarial Corruption
Theoretical Foundations of $\max$ @ $k$ Reinforcement Learning
Jul 20, 2026Riccardo Poiani, Martino Bernasconi, Andrea CelliOptimal Policies Top-K
Non-Asymptotic Best Policy Identification Guarantees in Online Reinforcement Learning
Jul 19, 2026Joseph Lazzaro, Alessio Russo, Aldo PacchianoOptimal Policies Markov Decision Processes
Searching for Task-Specific Vision Paths: Evolutionary Block Pruning Across Vision-Language Models
Jul 19, 2026Tarun TomarLarge Vision Language Models Point-Vlms
From Optimal Policies to Individual Differences: Rethinking Reinforcement Learning for Biology
Jul 17, 2026Patrick Govoni, Palina Bartashevich, Clémence Bergerot +3Biological Optimal Policies
CASP: Learning-Augmented Offline Approximation with Verifiable Certificates and Bounded-Loss PAC Guarantees
Jul 16, 2026Haifeng Li, Mo HaiCertificates Learning-Augmented Algorithms
Learning Who to Treat When Treatment is Missing
Jul 15, 2026Johnna Sundberg, Rayid Ghani, Eli Ben-Michael +1Heterogeneous Treatment Effects Missing Data
Equilibrium stability as a driver of cooperation among Q-learners
Jul 15, 2026Janusz M. Meylahn, Maximilian SchäferAlgorithmic Collusion Cooperation
Learning to Fine-tune Foundation Models under Resource Limitations
Jul 12, 2026Thomas Tsouparopoulos, Iordanis KoutsopoulosContinual Fine-Tuning Wireless Foundation Models
Offline Nash Solvers Meet Online Tree Search in Multi-Agent Games on Graphs
Jul 9, 2026Mukesh Kumar, Yue Guan, Panagiotis TsiotrasNash Equilibrium Multi-Agent Path Finding
Provably Optimal Learning Algorithms for Assistance Games
Jul 9, 2026Nivasini Ananthakrishnan, Mark Bedaywi, Michael I. Jordan +2Multi-Agent Reinforcement Learning Optimal Policies
CDCP: Conditional Diffusion Model with Contextual Prompts for Multi-task Offline Safe Reinforcement Learning
Jul 4, 2026Jiayi Guan, Tianle Zhang, Li Shen +8Offline Reinforcement Learning Discrete Diffusion Model
A Hierarchy of Policy Learning Problems
Jul 3, 2026Hamsa Bastani, Osbert Bastani, Shihan ChenOptimal Policies Linear Regret
ACPO: Adaptive Credit Policy Optimization via Fine-Grained Surrogate Entropy
Jul 3, 2026Zijun Xie, Yuyang You, Yongzhi Li +6Credit Assignment Entropy-Regularized Equilibrium Selection
Priced Motion Through Optimal Faces: A Normal-Fan Geometry for Non-Stationary Adversarial MDPs
Jun 27, 2026Kai HidajatOptimal Policies Markov Decision Processes
Learning in Markovian bandits with non-observable states and constrained decision epochs
Jun 25, 2026Thomas Hira, Victor Boone, Urtzi Ayesta +1O(T^Β)$ Simultaneous Regret Markov Decision Processes
Asymptotically Optimal Learning for Parametric Prophet Inequalities
Jun 25, 2026Jung-hun Kim, Anna Grebennikova, Vianney PerchetConcentration Inequalities Optimal Policies
Mean-Field PhiBE: Continuous-Time Mean-Field Reinforcement Learning from Discrete-Time Data
Jun 25, 2026Erhan Bayraktar, Martin Hernandez, Qinxin Yan +1Model-Free Reinforcement Learning Stochastic Optimal Control
Deterministic Pareto-Optimal Policy Synthesis for Multi-Objective Reinforcement Learning
Jun 24, 2026Aniruddha Joshi, Niklas Lauffer, Sanjit SeshiaConstrained Reinforcement Learning Optimal Policies
Low-Complexity Policy Tessellations in Structured Markov Decision Processes
Jun 24, 2026Fredy PokouMarkov Decision Processes Optimal Policies
Stationary Robust Mean-Field Games under Model Mismatches
Jun 21, 2026Yue WangMulti-Agent Reinforcement Learning Zero--Sum Differential Game
PolicyTrim: Boosting Intrinsic Policy Efficiency of Vision-Language-Action Models
Jun 21, 2026Xianghui Wang, Feng Chen, Wenbo Zhang +4Vision-Language-Action Models Inference Latency
Sequential Hiring of Contingent Workers Through Learning-Based Optimization
Jun 16, 2026Chris Lee, Xiuli Chao, Izak DuenyasStochastic Delays Optimal Bandit Algorithms
Learning Fair Pareto-Optimal Policies in Multi-Objective Reinforcement Learning
Jun 16, 2026Umer Siddique, Peilang Li, Yongcan CaoConstrained Reinforcement Learning Optimal Policies
Towards Pareto-Optimal Tool-Integrated Agents with Pareto Ranking Policy Optimization
Jun 15, 2026Junyi Li, Xiaowei Qian, Yingyi Zhang +6Multi-Turn Tool-Use Agent Value Alignment
Scalar-Stepsize Nonuniform Monte Carlo Optimistic Policy Iteration: A Certified Counterexample
Jun 14, 2026Yuanlong ChenStochastic Approximation Optimal Policies
Deterministic Policy Gradient for Learning Equilibrium in Time-Inconsistent Control Problems
Jun 10, 2026Xin Guo, Yijie Huang, Xiang YuOptimal Policies Optimal Control
Convergence of Monte Carlo Optimistic Policy Iteration: Beyond Uniform State-Action Updates
Jun 9, 2026Octave Oliviers, Glenn VinnicombeOptimal Policies Monte Carlo
Taiji: Pareto Optimal Policy Optimization with Semantics-IDs Trade-off for Industrial LLM-Enhanced Recommendation
Jun 2, 2026Yuecheng Li, Zeyu Song, Jing Yao +3Recommendation Industrial
SEArch: Optimistic Policy Selection Between Scene Noise and Drift for UAV Radar Search
May 31, 2026Noor Khial, Naram Mhaisen, Loay Ismail +1Unmanned Aerial Vehicles Radar
Decision-Focused On-Policy Learning for Contextual Linear Optimization with Partial Feedback
May 31, 2026Wyame Benslimane, Tinghan Ye, Pascal Van Hentenryck +1Linear Contextual Bandits Optimal Policies
Auditing Near-Optimal Policies Can Be Exponentially Hard: Conditional Query Lower Bounds via Occupancy Rashomon Capacity
May 29, 2026Ibne Farabi Shihab, Sanjeda Akter, Anuj SharmaAlgorithm Auditing Optimal Policies
Reinforcement Learning with Pairwise Preferences in Long-Term Decision Problems
May 29, 2026Jonathan Colaço Carr, Prakash Panangaden, Doina Precup +1Markov Decision Processes Optimal Policies
Safe Equilibrium Policy Optimization for Strategic Agent Policies
May 29, 2026Karthika Arumugam, Kiran Kumar Manku, Amit DhandaGroup Relative Policy Optimization Optimal Policies
Certified Policy Optimisation for Nested Causal Bandits via PAC-Bayes Risk
May 28, 2026Tim Woydt, Paul-David ZuercherOptimal Policies Thompson Sampling
The Sample Complexity of Multiclass and Sparse Contextual Bandits
May 28, 2026Liad Erez, Fan Chen, Alon Cohen +4Linear Contextual Bandits Sample Complexity
Variance-Adaptive Optimal Algorithm for Reinforcement Learning with Multinomial Logit Function Approximation
May 27, 2026Wonyoung Kim, Min-Hwan Oh, Garud Iyengar +1Near-Optimal Regret Guarantees Markov Decision Processes
Commit to the Bit: Reactive Reinforcement Learning Done Right
May 27, 2026Onno Eberhard, Claire Vernade, Michael MuehlebachQ-Learning Markov Decision Processes
Learning to Bid in Repeated Second-Price Auctions with Dynamic Values and Aggregated Feedback
May 27, 2026Benjamin Heymann, Otmane SakhiFirst-Price Auctions Optimal Policies
Human Decision-Making with AI Assistance under Correlated Features
May 27, 2026Yanru Guan, Naveen Raman, Fei FangSequential Decision Making Spurious Correlations
Reinforcement Learning for Reachability: Guaranteeing Asymptotic Optimality
May 23, 2026Amogh Palasamudram, Jakub Svoboda, Suguman Bansal +1Optimal Policies Reachability
Pure Exploration for a Good Policy in Reinforcement Learning with Bandit Feedback
May 22, 2026Zitian Li, Wang Chi CheungOptimal Policies Bandits

Sep 16, 2026 · econ.EMJ/K move · Enter open · S save

Stable Policy Learning

Harvey Barnhard, Giacomo Opocher, Rahul Singh

Harvard University · University of Mannheim

In evidence-based policymaking, typically one experimental sample is observed, then a learned policy recommendation is implemented at scale. Policies learned from the experimental data can perform well in expected welfare, yet random sampling in the experiment can produce recommendations with poor welfare outcomes. In this paper, we ask: how should policy learning algorithms balance expected welfare against sampling risk? Our main contribution is to show that algorithmic stability plays a central role in characterizing and navigating the tradeoff. Intuitively, if a policy learning algorithm's recommendation remains stable when one experimental unit is replaced, then that algorithm has limited sampling risk. We propose a method for policy learning called policy-vote bagging, which learns treatment decisions on many subsamples then averages their votes into treatment probabilities. Relative to using one subsample, averaging across subsamples preserves expected welfare and improves expected utility for a risk-averse researcher. We derive sharp bounds linking estimation accuracy, subsample size, and welfare variation, including an exact guarantee under CARA utility.

Optimal Policies Importance Sampling Welfare Decision Trees

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