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Choosing how much noise to add in Langevin dynamics is essential for making these algorithms effective in challenging optimization problems. One promising approach is to determine this noise by solving Hamilton-Jacobi-Bellman (HJB)…

Numerical Analysis · Mathematics 2026-03-19 Taorui Wang , Xun Li , Gu Wang , Zhongqiang Zhang

This paper develops a framework for establishing the existence of solutions to the equilibrium Hamilton-Jacobi-Bellman (EHJB) equation arising in time-inconsistent stochastic control problems. The time-inconsistency in our setting arises…

Optimization and Control · Mathematics 2026-04-07 Zhenhua Wang , Xiang Yu , Jingjie Zhang , Zhou Zhou

We solve explicitly a two-dimensional singular control problem of finite fuel type for infinite time horizon. The problem stems from the optimal liquidation of an asset position in a financial market with multiplicative and transient price…

Probability · Mathematics 2019-06-27 Dirk Becherer , Todor Bilarev , Peter Frentrup

We apply the stochastic Perron method of Bayraktar and S\^irbu to a general infinite horizon optimal control problem, where the state $X$ is a controlled diffusion process, and the state constraint is described by a closed set. We prove…

Optimization and Control · Mathematics 2014-09-25 Dmitry B. Rokhlin

Motivated by a control problem of a certain queueing network we consider a control problem where the dynamics is constrained in the nonnegative orthant $\mathbb{R}_+$ of the $d$-dimensional Euclidean space and controlled by the reflections…

Optimization and Control · Mathematics 2016-11-29 Anup Biswas , Hitoshi Ishii , Subhamay Saha , Lin Wang

We study the homogenization of first-order Hamilton-Jacobi equations on an infinite-dimensional Hilbert space, motivated by systems of infinitely many indistinguishable particles on the torus. A central difficulty is that the analysis takes…

Analysis of PDEs · Mathematics 2026-05-22 Seho Park

In this paper, we guarantee the existence and uniqueness (in the almost everywhere sense) of the solution to a Hamilton-Jacobi-Bellman (HJB) equation with gradient constraint and a partial integro-differential operator whose L\'evy measure…

Analysis of PDEs · Mathematics 2019-03-26 Mark Kelbert , Harold A. Moreno-Franco

We deal with an infinite horizon, infinite dimensional stochastic optimal control problem arising in the study of economic growth in time-space. Such problem has been the object of various papers in deterministic cases when the possible…

Optimization and Control · Mathematics 2022-03-14 Fausto Gozzi , Marta Leocata

In this paper infinite horizon optimal control problems for nonlinear high-dimensional dynamical systems are studied. Nonlinear feedback laws can be computed via the value function characterized as the unique viscosity solution to the…

Optimization and Control · Mathematics 2016-02-22 Alessandro Alla , Maurizio Falcone , Stefan Volkwein

A learning technique for finite horizon optimal control problems and its approximation based on polynomials is analyzed. It allows to circumvent, in part, the curse dimensionality which is involved when the feedback law is constructed by…

Optimization and Control · Mathematics 2023-02-21 Karl Kunisch , Donato Vásquez-Varas

In this paper, a class of high order numerical schemes is proposed for solving Hamilton-Jacobi (H-J) equations. This work is regarded as an extension of our previous work for nonlinear degenerate parabolic equations, see Christlieb et al.…

Numerical Analysis · Mathematics 2019-01-30 Andrew Christlieb , Wei Guo , Yan Jiang

Motivated by parallels between mean field games and random matrix theory, we develop stochastic optimal control problems and viscosity solutions to Hamilton-Jacobi equations in the setting of non-commutative variables. Rather than real…

Analysis of PDEs · Mathematics 2025-02-25 Wilfrid Gangbo , David Jekel , Kyeongsik Nam , Aaron Z. Palmer

We show that the value function of a stochastic control problem is the unique solution of the associated Hamilton-Jacobi-Bellman (HJB) equation, completely avoiding the proof of the so-called dynamic programming principle (DPP). Using…

Probability · Mathematics 2013-09-25 Erhan Bayraktar , Mihai Sirbu

We study a stochastic optimal control problem for a partially observed diffusion. By using the control randomization method in [4], we prove a corresponding randomized dynamic programming principle (DPP) for the value function, which is…

Probability · Mathematics 2016-09-12 Elena Bandini , Andrea Cosso , Marco Fuhrman , Huyên Pham

In this paper, we study ergodic backward stochastic differential equations (EBSDEs for short), for which the underlying diffusion is assumed to be multiplicative and of at most linear growth. The fact that the forward process has an…

Probability · Mathematics 2018-01-08 Ying Hu , Florian Lemonnier

Controlling the stochastic dynamics of biological populations is a challenge that arises across various biological contexts. However, these dynamics are inherently nonlinear and involve a discrete state space, i.e., the number of molecules,…

Populations and Evolution · Quantitative Biology 2025-10-21 Shuhei A. Horiguchi , Tetsuya J. Kobayashi

This work reformulates language generation as a stochastic optimal control problem, providing a unified theoretical perspective to analyze autoregressive and diffusion models and explain their limitations (Efficiency-Fidelity Paradox,…

Computation and Language · Computer Science 2026-05-18 ZiYi Dong , Yuliang Huang , Weijian Deng , Xiangyang Ji , Liang Lin , Pengxu Wei

We design fast numerical methods for Hamilton-Jacobi equations in density space (HJD), which arises in optimal transport and mean field games. We overcome the curse-of-infinite-dimensionality nature of HJD by proposing a generalized Hopf…

Numerical Analysis · Mathematics 2018-05-07 Yat Tin Chow , Wuchen Li , Stanley Osher , Wotao Yin

In this article we study a finite horizon optimal control problem with monotone controls. We consider the associated Hamilton-Jacobi-Bellman (HJB) equation which characterizes the value function. We consider the totally discretized problem…

Optimization and Control · Mathematics 2014-07-08 Eduardo A. Philipp , Laura S. Aragone , Lisandro A. Parente

We present a theory of optimal control for McKean-Vlasov stochastic differential equations with infinite time horizon and discounted gain functional. We first establish the well-posedness of the state equation and of the associated control…

Optimization and Control · Mathematics 2025-03-27 Silvia Rudà
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