Decision-Making under Uncertainty

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Decision-making under uncertainty studies how agents should choose actions when outcomes, states, preferences, or even the governing model are imperfectly known. Common approaches include Bayesian beliefs and partially observable Markov decision processes for sequential learning, robust optimization for misspecified distributions, risk-sensitive criteria such as CVaR, and conformal methods that calibrate when to act, gather information, or abstain. These methods are tested in settings such as autonomous driving and robotics, clinical diagnosis, energy and supply-chain scheduling, finance, and human–AI interaction. A central tension is that better-calibrated or more conservative uncertainty estimates do not automatically improve decisions: methods must balance safety and tail risk against utility, computational cost, and the value of additional information.

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204 papers24 papers in the last four weeks, up 26% on the four weeks before. 0.1% of all new papers.

Robust Out-of-Distribution Stochastic Optimization
Apr 22, 2026Xianyu Li, Huan Xu, Xiaolin Huang +1Stochastic Optimization OOD Generalization
Department of Automation, Tsinghua University · Antai College of Economics & Management, Shanghai Jiao Tong University · Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University
Multistage Conditional Compositional Optimization
Apr 15, 2026Buse Şen, Yifan Hu, Daniel KuhnStochastic Optimization Decision-Making under Uncertainty
EPFL, Switzerland · Rutgers University, USA
Instantiating Bayesian CVaR lower bounds in Interactive Decision Making Problems
Apr 14, 2026Raghav Bongole, Tobias J. Oechtering, Mikael SkoglundGaussian Process Bandits Decision-Making under Uncertainty
Department of Information Science and Engineering (ISE), KTH Royal Institute of Technology
Deep Learning for Sequential Decision Making under Uncertainty: Foundations, Frameworks, and Frontiers
Apr 13, 2026I. Esra BuyuktahtakinReinforcement Learning Predict-Then-Optimize
Grado Department of Industrial and Systems Engineering, Virginia Tech Blacksburg, VA 24061, USA
Mapping High-Performance Regions in Battery Scheduling across Data Uncertainty, Battery Design, and Planning Horizons
Apr 12, 2026Jaime de Miguel Rodriguez, Artjom Vargunin, Brigitta Robin Raudne +3Power Systems Decision-Making under Uncertainty
Enefit, Estonia · University of Seville, Spain · University of Tartu, Estonia +1
The Theorems of Dr. David Blackwell and Their Contributions to Artificial Intelligence
Apr 8, 2026Napoleon PaxtonBlackwell Approachability Decision-Making under Uncertainty
School of Information, University of California, Berkeley
Noisy Nonreciprocal Pairwise Comparisons: Scale Variation, Noise Calibration, and Admissible Ranking Regions
Apr 6, 2026Jean-Pierre MagnotPairwise Comparison Decision-Making under Uncertainty
SFR MATHSTIC, LAREMA, Université d’Angers, 2 Bd Lavoisier, 49045 Angers cedex 1, France · Lycée Jeanne d’Arc, 40 avenue de Grande Bretagne, 63000 Clermont-Ferrand, France · Lepage Research Institute, 17 novembra 1, 081 16 Presov, Slovakia
Optimizing Service Operations via LLM-Powered Multi-Agent Simulation
Apr 6, 2026Yanyuan Wang, Xiaowei ZhangStochastic Optimization Decision-Making under Uncertainty
Department of Industrial Engineering and Decision Analytics, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong SAR
Generative models for decision-making under distributional shift
Apr 6, 2026Xiuyuan Cheng, Yunqin Zhu, Yao XieDecision-Making under Uncertainty Distribution Shift Robustness
Department of Mathematics, Duke University, Durham, NC, USA · H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, USA
Uncertainty as a Planning Signal: Multi-Turn Decision Making for Goal-Oriented Conversation
Apr 5, 2026Xinyi Ling, Ye Liu, Reza Averly +1Task-Oriented Dialogue Systems Decision-Making under Uncertainty
Department of Computer Science and Engineering, The Ohio State University · Department of Biomedical Informatics, The Ohio State University · Translational Data Analytics Institute, The Ohio State University
A Comprehensive Framework for Long-Term Resiliency Investment Planning under Extreme Weather Uncertainty for Electric Utilities
Apr 2, 2026Emma BenjaminsonPower Systems Decision-Making under Uncertainty
Boston Consulting Group’s AI Science Institute, Pittsburgh, PA, USA
Learning in Prophet Inequalities with Noisy Observations
Apr 2, 2026Jung-hun Kim, Vianney PerchetOptimal Stopping Decision-Making under Uncertainty
CREST, ENSAE, IP Paris · FairPlay joint team · Criteo AI Lab
All Substitution Is Local
Apr 1, 2026Nidhish Shah, Shaurjya Mandal, Asfandyar AzharValue of Information Bayesian Decision Theory
Harvard University · University of Oxford
Scenario theory for multi-criteria data-driven decision making
Apr 1, 2026Simone Garatti, Lucrezia Manieri, Alessandro Falsone +3Decision-Making under Uncertainty Multi-Criteria Decision Analysis
Dipartimento di Elettronica Informazione e Ingegneria, Politecnico di Milano, Milano, Italy · Dipartimento di Ingegneria dell’Informazione, Universit`a degli studi di Brescia, Brescia, Italy
UMBRELLA: Uncertainty-aware Multi-robot Reactive Coordination under Dynamic Temporal Logic Tasks
Mar 26, 2026Qisheng Zhao, Meng Guo, Hengxuan Du +2Risk-Sensitive Planning Multi-Robot Coordination
School of Advanced Manufacturing and Robotics, Peking University, Beijing 100871, China · Automatic Control Laboratory, ETH Zürich, Zürich 8092, Switzerland
The Value of Information in Resource-Constrained Pricing
Mar 26, 2026Ruicheng Ao, Jiashuo Jiang, David Simchi-LeviDynamic Pricing Decision-Making under Uncertainty
Institute for Data, Systems, and Society, Massachusetts Institute of Technology · Department of Industrial Engineering and Decision Analytics, Hong Kong University of Science and Technology · Department of Civil and Environmental Engineering and Operations Research Center, MIT
Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation in an Uncertain Enterprise Environment
Mar 24, 2026Yi Han, Yan Wang, Lingfei Qian +12Long-Horizon Agent Evaluation LLM Agents
Georgia Institute of Technology · The Fin AI · Stevens Institute of Technology +7
A Bayesian Learning Approach for Drone Coverage Network: A Case Study on Cardiac Arrest in Scotland
Mar 24, 2026Tathagata Basu, Edoardo Patelli, Gianluca Filippi +7Healthcare Decision-Making under Uncertainty
UNSW Bengaluru, Bengaluru, India · Civil and Environmental Engineering, University of Strathclyde, Glasgow G1 1XQ, UK · Centre for Maritime Research and Experimentation, 19126 La Spezia, Italy +2
Multi-Robot Learning-Informed Task Planning Under Uncertainty
Mar 20, 2026Abhish Khanal, Abhishek Paudel, Hung Pham +1Multi-Robot Coordination Decision-Making under Uncertainty
Department of Computer Science, George Mason University, Fairfax, VA, 22030, USA.
Contextual Preference Distribution Learning
Mar 17, 2026Benjamin Hudson, Laurent Charlin, Emma FrejingerPreference Learning Decision-Making under Uncertainty
Mila – Quebec Artificial Intelligence Institute, Montreal, Quebec, Canada · Département d’informatique et de recherche opérationnelle (DIRO), Université de Montréal, Montreal, Quebec, Canada · HEC Montréal, Montreal, Quebec, Canada
Persona-Conditioned Risk Behavior in Large Language Models: A Simulated Gambling Study with GPT-4.1
Mar 16, 2026Sankalp DubedyProspect Theory LLM Decision-Making
Independent Researcher
Survey of Various Fuzzy and Uncertain Decision-Making Methods
Mar 16, 2026Takaaki Fujita, Florentin SmarandacheDecision-Making under Uncertainty Multi-Criteria Decision Analysis
Neutrosophic Science International Association (NSIA) Publishing House Gallup - Guayaquil United States of America – Ecuador
Chance-Constrained Correlated Equilibria for Robust Noncooperative Coordination
Mar 14, 2026Jaehan Im, Ufuk Topcu, David Fridovich-KeilGame Theory Decision-Making under Uncertainty
Department of Aerospace Engineering and Engineering Mechanics, The University of Texas at Austin · The Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin
Distributional Uncertainty and Adaptive Decision-Making in System Co-design
Mar 14, 2026Yujun Huang, Gioele ZardiniDecision-Making under Uncertainty Uncertainty Quantification
Laboratory for Information & Decision Systems, Massachusetts Institute of Technology, Cambridge, MA 02139
Adaptive Conditional Residual Sampling for Spectral Risk Optimisation under Decision-Dependent Uncertainty
Mar 12, 2026Marcell T. KurbuczStochastic Optimization Decision-Making under Uncertainty
Institute for Global Prosperity, The Bartlett, University College London, 9–11 Endsleigh Gardens, London, WC1H 0EH, United Kingdom
Optimizing Task Completion Time Updates Using POMDPs
Mar 12, 2026Duncan Eddy, Esen Yel, Emma Passmore +4Decision-Making under Uncertainty
Stanford University, Stanford, CA, USA · Rensselaer Polytechnic Institute, Troy, NY, USA
Safe RLHF Beyond Expectation: Stochastic Dominance for Universal Spectral Risk Control
Mar 11, 2026Yaswanth Chittepu, Ativ Joshi, Rajarshi Bhattacharjee +1Constrained RL LLM Safety Alignment
University of Massachusetts Amherst
Implicit Statistical Inference in Transformers: Approximating Likelihood-Ratio Tests In-Context
Mar 11, 2026Faris Chaudhry, Siddhant GadkariLikelihood Ratio Testing In-Context Learning
Department of Computer Science Imperial College London
Noncooperative Human-AI Agent Dynamics
Mar 10, 2026Dylan Waldner, Vyacheslav Kungurtsev, Mitchelle AshimosiProspect Theory Human-AI Decision Making
The Confidence Gate Theorem: When Should Ranked Decision Systems Abstain?
Mar 10, 2026Ronald DokuDecision-Making under Uncertainty Uncertainty Quantification
Haske Labs

Apr 22, 2026J/K move · Enter open · S save

Robust Out-of-Distribution Stochastic Optimization

Xianyu Li, Huan Xu, Xiaolin Huang, Chao Shang

Department of Automation, Tsinghua University · Antai College of Economics & Management, Shanghai Jiao Tong University · Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University

Stochastic Optimization OOD Generalization Distributionally Robust Optimization Decision-Making under Uncertainty

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Data-driven decision-making under uncertainty typically presumes the collection of historical data from an unknown target probability distribution. However, one may have no access to any data from the target distribution prior to decision-making. To address this challenge, we propose robust out-of-distribution stochastic optimization, a novel data-driven framework that effectively utilizes relevant data distributions for robust decision-making under unseen distributions. A key feature of our framework is that all data distributions are assumed to be randomly generated from a meta-distribution over distributions. To describe uncertainty in distribution generation, we propose to learn a data-driven uncertainty set in a reproducing kernel Hilbert space (RKHS) from relevant data distributions, with adjustable conservatism. We then incorporate this set into a min-max stochastic program to derive robust decisions. Notably, under randomness of distribution generation, we establish rigorous out-of-distribution generalization guarantees for the uncertainty set as well as the solution. To ease problem-solving in RKHS, an approximate parametrization with a provably bounded suboptimality and a row generation strategy are presented. Extensive numerical experiments on multi-item newsvendor and portfolio optimization demonstrate the superior out-of-distribution performance of our decision-making framework under unseen data distribution, even when only a small or moderate number of relevant sources are available.