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This paper is concerned with the relationship between general maximum principle and dynamic programming principle for the stochastic recursive optimal control problem with jumps, where the control domain is not necessarily convex. Relations…

Optimization and Control · Mathematics 2024-06-04 Bin Wang , Jingtao Shi

This paper deals with a stochastic recursive optimal control problem, where the diffusion coefficient depends on the control variable and the control domain is not necessarily convex. We focus on the connection between the general maximum…

Optimization and Control · Mathematics 2016-12-21 Tianyang Nie , Jingtao Shi , Zhen Wu

This paper deals with a nonsmooth version of the connection between the maximum principle and dynamic programming principle, for the stochastic recursive control problem when the control domain is convex. By employing the notions of sub-…

Optimization and Control · Mathematics 2016-03-09 Tianyang Nie , Jingtao Shi , Zhen Wu

This paper is concerned with the relationship between maximum principle and dynamic programming principle for risk-sensitive stochastic optimal control problems. Under the smooth assumption of the value function, relations among the adjoint…

Optimization and Control · Mathematics 2025-07-10 Huanqing Dong , Jingtao Shi

In this paper, we study the relationship between maximum principle (MP) and dynamic programming principle (DPP) for stochastic recursive optimal control problem driven by $G$-Brownian motion. Under the smooth assumption for the value…

Optimization and Control · Mathematics 2022-10-12 Xiaojuan Li

Within the framework of viscosity solution, we study the relationship between the maximum principle (MP) in [9] and the dynamic programming principle (DPP) in [10] for a fully coupled forward-backward stochastic controlled system (FBSCS)…

Optimization and Control · Mathematics 2018-05-17 Mingshang Hu , Shaolin Ji , Xiaole Xue

In this paper, we study the relationship between maximum principle (MP) and dynamic programming principle (DPP) for forward-backward control system under consistent convex expectation dominated by G-expectation. Under the smooth assumptions…

Optimization and Control · Mathematics 2024-09-18 Xiaojuan Li , Mingshang Hu

This paper aims to study the relationship between the maximum principle and the dynamic programming principle for recursive optimal control problem of stochastic evolution equations, where the control domain is not necessarily convex and…

Optimization and Control · Mathematics 2025-12-19 Ying Hu , Guomin Liu , Shanjian Tang

This paper aims to explore the relationship between maximum principle and dynamic programming principle for stochastic recursive control problem with random coefficients. Under certain regular conditions for the coefficients, the…

Optimization and Control · Mathematics 2020-12-10 Yuchao Dong , Qingxin Meng , Qi Zhang

We construct an abstract framework in which the dynamic programming principle (DPP) can be readily proven. It encompasses a broad range of common stochastic control problems in the weak formulation, and deals with problems in the…

Optimization and Control · Mathematics 2019-06-04 Roman Fayvisovich , Gordan Zitkovic

Pontryagin type maximum principle and Bellman's dynamic programming principle serve as two of the most important tools in solving optimal control problems. There is a huge literature on the study of relationship between them. The main…

Optimization and Control · Mathematics 2021-12-30 Liangying Chen , Qi Lü

This paper investigates the relationship between Pontryagin's maximum principle and dynamic programming principle in the context of stochastic optimal control systems governed by stochastic evolution equations with random coefficients in…

Optimization and Control · Mathematics 2025-11-05 Dingqian Gao , Qi Lü

This paper is concerned with the stochastic recursive optimal control problem with mixed delay. The connection between Pontryagin's maximum principle and Bellman's dynamic programming principle is discussed. Without containing any…

Optimization and Control · Mathematics 2019-12-24 Weijun Meng , Jingtao Shi

We analyze an optimal stopping problem with a constraint on the expected cost. When the reward function and cost function are Lipschitz continuous in state variable, we show that the value of such an optimal stopping problem is a continuous…

Optimization and Control · Mathematics 2017-08-08 Erhan Bayraktar , Song Yao

Since Peng (1993) established a local maximum principle for a general stochastic control problem governed by forward-backward stochastic differential equations (FBSDEs), the corresponding partial differential equation (PDE) characterization…

Optimization and Control · Mathematics 2025-08-07 Yuhong Xu , Shuzhen Yang

In this paper, we study one kind of stochastic recursive optimal control problem with the obstacle constraints for the cost function where the cost function is described by the solution of one reflected backward stochastic differential…

Optimization and Control · Mathematics 2007-05-23 Zhen Wu , Zhiyong Yu

In this work we introduce a viscosity-based notion of solution for general approximation schemes associated with partial differential equations, such as dynamic programming principles~(DPPs). A key feature of our approach is that it…

Analysis of PDEs · Mathematics 2026-02-11 Félix del Teso , Julio D. Rossi , Jorge Ruiz-Cases

In this paper, we study the delayed stochastic recursive optimal control problem with a non-Lipschitz generator, in which both the dynamics of the control system and the recursive cost functional depend on the past path segment of the state…

Optimization and Control · Mathematics 2023-12-27 Jiaqiang Wen , Zhen Wu , Qi Zhang

We study the optimal control of general stochastic McKean-Vlasov equation. Such problem is motivated originally from the asymptotic formulation of cooperative equilibrium for a large population of particles (players) in mean-field…

Probability · Mathematics 2017-01-06 Huyên Pham , Xiaoli Wei

In this paper, we study a stochastic recursive optimal control problem in which the cost functional is described by the solution of a backward stochastic differential equation driven by G-Brownian motion. Under standard assumptions, we…

Optimization and Control · Mathematics 2014-10-15 Mingshang Hu , Shaolin Ji
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