A stochastic maximum principle for switching diffusions using conditional mean-fields with applications to control problems

2020 ◽  
Vol 26 ◽  
pp. 69 ◽  
Author(s):  
Son L. Nguyen ◽  
Dung T. Nguyen ◽  
George Yin
Keyword(s):  
Maximum Principle ◽  
Large Scale ◽  
Mean Field ◽  
Control Problems ◽  
Optimal Controls ◽  
Linear Quadratic ◽  
Conditional Mean ◽  
Switching Diffusions ◽  
Wide Range ◽  
Mean Fields

This paper obtains a maximum principle for switching diffusions with mean-field interactions. The motivation stems from a wide range of applications for networked control systems in which large-scale systems are encountered and mean-field interactions are involved. Because of the complexity due to the switching, little has been done for the associate control problems with mean-field interactions. The main ingredient of this work is the use of conditional mean-fields, which is distinct from the existing literature. Using the maximum principle, optimal controls of linear quadratic Gaussian controls with mean-field interactions for switching diffusions are carried out. Numerical examples are also provided for demonstration.

On closed-loop equilibrium strategies for mean-field stochastic linear quadratic problems

2020 ◽  
Vol 26 ◽  
pp. 41
Author(s):  
Tianxiao Wang
Keyword(s):  
Optimal Control ◽  
Closed Loop ◽  
Optimal Control Problems ◽  
Mean Field ◽  
Open Loop ◽  
Time Inconsistency ◽  
Control Problems ◽  
Linear Quadratic ◽  
Linear Quadratic Optimal Control ◽  
Equilibrium Strategies

This article is concerned with linear quadratic optimal control problems of mean-field stochastic differential equations (MF-SDE) with deterministic coefficients. To treat the time inconsistency of the optimal control problems, linear closed-loop equilibrium strategies are introduced and characterized by variational approach. Our developed methodology drops the delicate convergence procedures in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. When the MF-SDE reduces to SDE, our Riccati system coincides with the analogue in Yong [Trans. Amer. Math. Soc. 369 (2017) 5467–5523]. However, these two systems are in general different from each other due to the conditional mean-field terms in the MF-SDE. Eventually, the comparisons with pre-committed optimal strategies, open-loop equilibrium strategies are given in details.

Linear quadratic control problems of stochastic Volterra integral equations

2018 ◽  
Vol 24 (4) ◽  
pp. 1849-1879 ◽  
Author(s):  
Tianxiao Wang
Keyword(s):  
Integral Equations ◽  
Stochastic Systems ◽  
Open Loop ◽  
Volterra Integral Equations ◽  
Control Problems ◽  
Optimal Controls ◽  
Linear Quadratic Control ◽  
Linear Quadratic ◽  
The Cost ◽  
Quadratic Control Problems

This paper is concerned with linear quadratic control problems of stochastic differential equations (SDEs, in short) and stochastic Volterra integral equations (SVIEs, in short). Notice that for stochastic systems, the control weight in the cost functional is allowed to be indefinite. This feature is demonstrated here only by open-loop optimal controls but not limited to closed-loop optimal controls in the literature. As to linear quadratic problem of SDEs, some examples are given to point out the issues left by existing papers, and new characterizations of optimal controls are obtained in different manners. For the study of SVIEs with deterministic coefficients, a class of stochastic Fredholm−Volterra integral equations is introduced to replace conventional forward-backward SVIEs. Eventually, instead of using convex variation, we use spike variation to obtain some additional optimality conditions of linear quadratic problems for SVIEs.

Sign in / Sign up

Export Citation Format

Share Document