标题:Partial information differential games for mean-field SDEs
作者:Xiao, Hua ;Zhang, Shuaiqi
作者机构:[Xiao, Hua ] School of Mathematics and Statistics, Shandong University, Weihai; 264209, China;[Zhang, Shuaiqi ] School of Economics and Commerce, Guan 更多
会议名称:35th Chinese Control Conference, CCC 2016
会议日期:27 July 2016 through 29 July 2016
来源:Chinese Control Conference, CCC
出版年:2016
卷:2016-August
页码:1684-1689
DOI:10.1109/ChiCC.2016.7553334
关键词:Backward stochastic differential equations; Maximum principle; Mean-field games; Partial information; Verification
摘要:This paper is concerned with non-zero sum differential games of mean-field stochastic differential equations with partial information and convex control domain. First, applying the classical convex variations, we obtain stochastic maximum principle for Nash equilibrium points. Subsequently, under additional assumptions, verification theorem for Nash equilibrium points is also derived. Finally, as an application, a linear quadratic example is discussed. The unique Nash equilibrium point is represented in a feedback form of not only the optimal filtering but also expected value of the system state, throughout the solutions of the Riccati equations. © 2016 TCCT.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84987911846&doi=10.1109%2fChiCC.2016.7553334&partnerID=40&md5=fde249c813152bbfb9413144e30b9941
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