Stochastic Optimal Control

Latest papers 91

12 papers in the last four weeks, up 33% on the four weeks before. 0.1% of all new papers.

Continuous-time q-learning for mean-field control with common noise, part-I: Theoretical foundations
Apr 30, 2026Zhenjie Ren, Xiaoli Wei, Xiang Yu +1Stochastic Optimal Control Q-Learning
LaMME, Universit´e ´Evry Paris-Saclay, ´Evry, France · Department of Applied Mathematics, The Hong Kong Polytechnic University, Kowloon, Hong Kong · Department of Industrial Engineering and Operations Research, Columbia University, New York, USA
Learning to Spend: Model Predictive Control for Budgeting under Non-Stationary Returns
Apr 29, 2026Nilavra Pathak, Smriti Shyamal, Prasant Mhasker +1Stochastic Optimal Control Model Predictive Control
Marketing Data Science, Expedia Group · Department of Chemical Engineering, McMaster University
Nonlinear Non-Gaussian Density Steering with Input and Noise Channel Mismatch: Sinkhorn with Memory for Solving the Control-affine Schrödinger Bridge Problem
Apr 25, 2026Georgiy A. Bondar, Asmaa Eldesoukey, Yongxin Chen +1Stochastic Optimal Control Schrödinger Bridges
Department of Aerospace Engineering, Iowa State University, Ames, IA 50011, USA · School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
Iterative Model-Learning Scheme via Gaussian Processes for Nonlinear Model Predictive Control of (Semi-)Batch Processes
Apr 24, 2026Tai Xuan Tan, Alexander Mitsos, Eike CramerNonlinear MPC Stochastic Optimal Control
Process Systems Engineering (AVT.SVT), RWTH Aachen University, Forckenbeckstraße 51, 52074 Aachen, Germany · JARA-CSD, 52056 Aachen, Germany · Institute of Climate and Energy Systems: Energy Systems Engineering (ICE-1), Forschungszentrum Jülich GmbH, 52425 Jülich, Germany +1
Rate-Optimal Regret for the Safe Learning-based Control of the Constrained Linear Quadratic Regulator
Apr 24, 2026Spencer Hutchinson, Nanfei Jiang, Mahnoosh AlizadehStochastic Linear Dynamical Systems Stochastic Optimal Control
Department of Electrical and Computer Engineering, University of California Santa Barbara
SLAM as a Stochastic Control Problem with Partial Information: Optimal Solutions and Rigorous Approximations
Apr 23, 2026Ilir Gusija, Fady Alajaji, Serdar YükselSimultaneous Localization and Mapping Stochastic Optimal Control
Department of Mathematics and Statistics, Queen’s University, Kingston, ON, Canada
Rare Event Analysis via Stochastic Optimal Control
Apr 14, 2026Yuanqi Du, Jiajun He, Dinghuai Zhang +2Rare-Event Estimation Stochastic Optimal Control
Microsoft Research New England · Cornell University · University of Cambridge +1
Adaptive Learning via Off-Model Training and Importance Sampling for Fully Non-Markovian Optimal Stochastic Control. Complete version
Apr 14, 2026Dorival Leão, Alberto Ohashi, Simone Scotti +1Stochastic Optimal Control Adaptive Learning
Density-Driven Optimal Control: Convergence Guarantees for Stochastic LTI Multi-Agent Systems
Apr 9, 2026Kooktae LeeMulti-Agent Control Stochastic Optimal Control
Department of Mechanical Engineering, New Mexico Institute of Mining and Technology, Socorro, NM 87801, USA
Generative optimal transport via forward-backward HJB matching
Apr 9, 2026Haiqian Yang, Vishaal Krishnan, Sumit Sinha +1Stochastic Optimal Control Optimal Transport
Department of Mechanical Engineering, MIT, Cambridge, MA 02139 · SEAS, Harvard University, Cambridge, MA 02138 · SEAS, Physics and OEB, Harvard University, Cambridge, MA 02138
An Actor-Critic Framework for Continuous-Time Jump-Diffusion Controls with Normalizing Flows
Apr 7, 2026Liya Guo, Ruimeng Hu, Xu Yang +1Stochastic Optimal Control Actor-Critic Methods
Department of Mathematics, Tsinghua University, Beijing 100084, China · Department of Mathematics, and Department of Statistics and Applied Probability, University of California, Santa Barbara, CA 93106-3080, USA · Department of Mathematics, University of California, Santa Barbara, CA 93106-3080, USA +1
Separation is Optimal for LQR under Intermittent Feedback
Mar 29, 2026Abdullah Y. Etcibasi, C. Emre Koksal, Eylem EkiciSequential Decision Making Stochastic Optimal Control
The Ohio State University
Adjoint Matching through the Lens of the Stochastic Maximum Principle in Optimal Control
Mar 28, 2026Carles Domingo-Enrich, Jiequn HanStochastic Optimal Control Optimal Control
Microsoft Research New England · Flatiron Institute
A Schrödinger Eigenfunction Method for Long-Horizon Stochastic Optimal Control
Mar 24, 2026Louis Claeys, Artur Goldman, Zebang Shen +1Stochastic Optimal Control Linear Quadratic Regulator
ETH Zürich, Department of Mathematics · ETH Zürich, ETH AI Center, Institute for Machine Learning · ETH Zürich, Institute for Machine Learning
Infinite-dimensional spherical-radial decomposition for probabilistic functions, with application to constrained optimal control and Gaussian process regression
Mar 20, 2026Kewei Wang, Georg StadlerChance-Constrained Optimization Stochastic Optimal Control
Courant Institute School of Mathematics, Computing and Data Science, New York University, New York, USA
Deep Hilbert--Galerkin Methods for Infinite-Dimensional PDEs and Optimal Control
Mar 19, 2026Samuel N. Cohen, Filippo de Feo, Jackson Hebner +1Neural PDE Solvers PDE Solving
Mathematical Institute, University of Oxford · Institut für Mathematik, Technische Universität Berlin
Exact and Approximate Convex Reformulation of Linear Stochastic Optimal Control with Chance Constraints
Mar 19, 2026Tanmay Dokania, Yashwanth Kumar NakkaStochastic Optimal Control Chance-Constrained Optimization
Authors are with the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology, Atlanta, GA, 30332 USA.
Conservative Continuous-Time Treatment Optimization
Mar 17, 2026Nora Schneider, Georg Manten, Niki KilbertusStochastic Optimal Control
Technical University of Munich · Helmholtz Munich · Munich Center for Machine Learning
Schrödinger Bridge Over A Compact Connected Lie Group
Mar 14, 2026Hamza Mahmood, Abhishek Halder, Adeel AkhtarSchrödinger Bridges Stochastic Optimal Control
Department of Mechanical & Industrial Engineering at the New Jersey Institute of Technology, Newark, NJ 07102, USA · Department of Aerospace Engineering at Iowa State University, Ames, IA 50011, USA
Cost-Driven Representation Learning for Linear Quadratic Gaussian Control: Part II
Mar 8, 2026Yi Tian, Kaiqing Zhang, Russ Tedrake +1State Representation Learning Latent Dynamics Modeling
Massachusetts Institute of Technology · University of Maryland, College Park · Technical University Munich
Optimal trajectory-guided stochastic co-optimization for e-fuel system design and real-time operation
Mar 3, 2026Jeongdong Kim, Minsu Kim, Jonggeol Na +1Learning to Optimize Stochastic Optimization
Department of Chemical Engineering , Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, 02139, Massachusetts, United States. · Department of Chemical and Biomolecular Engineering, Yonsei University, 50 Yonsei-ro, Seoul, 03722, Republic of Korea. · Department of Chemical Engineering and Materials Science, Ewha Womans University, 52 Ewhayeodae-gil, Seoul, 03760, Republic of Korea. +2
RAmmStein: Regime Adaptation in Mean-reverting Markets with Stein Thresholds -- Optimal Impulse Control in Concentrated AMMs
Feb 23, 2026Pranay AnchuriDecentralized Finance Optimal Control
Offchain Labs
Convex Chance-Constrained Stochastic Control under Uncertain Specifications with Application to Learning-Based Hybrid Powertrain Control
Jan 26, 2026Teruki Kato, Ryotaro Shima, Kenji KashimaChance-Constrained Optimization Stochastic Optimal Control
Toyota Central R&D Labs., Inc., Nagakute, Aichi, Japan · Graduate School of Informatics, Kyoto University, Kyoto, Japan
Adaptive Partitioning and Learning for Stochastic Control of Diffusion Processes
Dec 17, 2025Hanqing Jin, Renyuan Xu, Yanzhao YangRL Control Reinforcement Learning
Mathematical Institute, University of Oxford · Department of Management Science and Engineering, Stanford University
Control Consistency Losses for Diffusion Bridges
Dec 4, 2025Samuel Howard, Nikolas Nüsken, Jakiw PidstrigachConditional Diffusion Models Stochastic Optimal Control
Department of Statistics, University of Oxford · Department of Mathematics, King’s College London
Infinitesimal Operator World Models: Finite-Sample Guarantees for Offline Reinforcement Learning
Nov 13, 2025Nicolas Hoischen, Petar Bevanda, Max Beier +3Offline RL Model-Based RL
TU Munich · ShanghaiTech University
Stein-based Optimization of Sampling Distributions in Model Predictive Path Integral Control
Nov 3, 2025Jace Aldrich, Odest Chadwicke JenkinsRobotic Control Stochastic Optimal Control
Laboratory for Perceptive RObotics and Grounded REasoning SystemS and Robotics Department at the University of Michigan, Ann Arbor, USA
Continuous Policy and Value Iteration for Stochastic Control Problems and Its Convergence
Jun 9, 2025Qi Feng, Gu WangStochastic Optimal Control Policy Iteration
Department of Mathematics, Florida State University, Tallahassee, 32306 · Department of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, MA 01609
Gaussian process policy iteration with additive Schwarz acceleration for forward and inverse HJB and mean field game problems
May 1, 2025Xianjin Yang, Jingguo ZhangMean Field Games Stochastic Optimal Control
Department of Computing and Mathematical Sciences, California Institute of Technology, CA, USA. · Department of Mathematics and Risk Management Institute, National University of Singapore, Singapore.
Rough Stochastic Pontryagin Maximum Principle and an Indirect Shooting Method
Feb 10, 2025Thomas LewStochastic Differential Equations Stochastic Optimal Control
Toyota Research Institute

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Continuous-time q-learning for mean-field control with common noise, part-I: Theoretical foundations

Zhenjie Ren, Xiaoli Wei, Xiang Yu, Xun Yu Zhou

LaMME, Universit´e ´Evry Paris-Saclay, ´Evry, France · Department of Applied Mathematics, The Hong Kong Polytechnic University, Kowloon, Hong Kong · Department of Industrial Engineering and Operations Research, Columbia University, New York, USA

Stochastic Optimal Control Q-Learning Maximum Entropy RL Mean-Field Theory Optimal Control

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This paper investigates the continuous-time counterpart of the Q-function for entropy-regularized mean-field control (MFC) with controlled common noise, coined as q-function by Jia and Zhou (2023) in the single agent's model. We first show that, under discretely sampled actions, the value function in the exploratory formulation converges to the one in the relaxed control formulation as the time grid refines. Leveraging the relaxed control formulation, we derive the exploratory Hamilton-Jacobi-Bellman (HJB) equation, in which the controlled common noise gives rise to an additional nonlinear functional of policy, rendering the policy iteration intricate. Under certain concavity condition, we establish the existence and uniqueness of the optimal one-step policy iteration via a first-order condition using the partial linear functional derivative with respect to policy. The policy improvement at each iteration is verified by relating to an entropy-regularized optimization problem over the space of policies. In the mean-field setting, we introduce the integrated q-function (Iq-function) defined on the state distribution and the policy, and it is shown that an optimal policy is identified as a two-layer fixed point to the argmax operator of the Iq-function. Finally, we provide the explicit characterization of an optimal policy as a Gaussian distribution in the general linear-quadratic (LQ) setting.