Title
Stochastic Maximum Principle for Mean-Field Type Optimal Control Under Partial Information
Abstract
This technical note is concerned with a partially observed optimal control problem, whose novel feature is that the cost functional is of mean-field type. Hence determining the optimal control is time inconsistent in the sense that Bellman's dynamic programming principle does not hold. A maximum principle is established using Girsanov's theorem and convex variation. Some nonlinear filtering results for backward stochastic differential equations (BSDEs) are developed by expressing the solutions of the BSDEs as some Itô's processes. An illustrative example is demonstrated in terms of the maximum principle and the filtering.
Year
DOI
Venue
2014
10.1109/TAC.2013.2273265
IEEE Trans. Automat. Contr.
Keywords
Field
DocType
Equations,Mathematical model,Optimal control,Standards,Educational institutions,Aerospace electronics,Differential equations
Differential equation,Dynamic programming,Mathematical optimization,Optimal control,Maximum principle,Filter (signal processing),Stochastic differential equation,Girsanov theorem,Convex optimization,Mathematics
Journal
Volume
Issue
ISSN
59
2
0018-9286
Citations 
PageRank 
References 
21
1.27
2
Authors
3
Name
Order
Citations
PageRank
Guangchen Wang115318.94
Chenghui Zhang226838.20
Weihai Zhang362567.73