Title
Connection between MP and DPP for Stochastic Recursive Optimal Control Problems: Viscosity Solution Framework in the General Case.
Abstract
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 principle and the dynamic programming principle for such a control problem without the assumption that the value is smooth enough; the set inclusions among the sub-and super-jets of the value function and the first-order and second-order adjoint processes as well as the generalized Hamiltonian function are established. Moreover, by comparing these results with the classical ones in Yong and Zhou [Stochastic Controls: Hamiltonian Systems and HJB Equations, Springer-Verlag, New York, 1999], it is natural to obtain the first- and second-order adjoint equations of Hu [Probability, Uncertainty and Quantitative Risk, 2 (2017), 1].
Year
DOI
Venue
2017
10.1137/16M1064957
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
Keywords
Field
DocType
stochastic recursive optimal control,backward stochastic differential equation,maximum principle,dynamic programming principle,subjets,superjets,viscosity solution
Hamilton–Jacobi–Bellman equation,Dynamic programming,Mathematical optimization,Optimal control,Maximum principle,Mathematical analysis,Hamiltonian system,Bellman equation,Hamiltonian mechanics,Viscosity solution,Mathematics
Journal
Volume
Issue
ISSN
55
5
0363-0129
Citations 
PageRank 
References 
1
0.36
0
Authors
3
Name
Order
Citations
PageRank
Tianyang Nie110.69
jingtao2406.42
Zhen Wu3237.12