A general maximum principle for partially observed mean-field stochastic system with random jumps in progressive structure | Zendy

Tian Chen | Zendy; Zhen Wu | Zendy

Open Access

A general maximum principle for partially observed mean-field stochastic system with random jumps in progressive structure

Author(s) -

Tian Chen,

Zhen Wu

Publication year - 2022

Publication title -

mathematical control and related fields

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.658

H-Index - 21

eISSN - 2156-8472

pISSN - 2156-8499

DOI - 10.3934/mcrf.2022012

Subject(s) - mathematics , maximum principle , mean field theory , jump , observable , jump diffusion , domain (mathematical analysis) , random field , optimal control , type (biology) , regular polygon , stochastic control , mathematical analysis , statistical physics , mathematical optimization , physics , statistics , geometry , quantum mechanics , ecology , biology

We study the progressive optimal control for partially observed stochastic system of mean-field type with random jumps. The cost function and the observation are also of mean-field type. The control is allowed to enter the diffusion, jump coefficient and the observation. The control domain need not be convex. We obtain the maximum principle for the partially observable progressive optimal control by a special spike variation. The maximum principle in the progressive structure is different from the classical case.

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