Necessary and sufficient conditions in optimal control of mean-field stochastic differential equations with infinite horizon

IF 0.3 Q4 STATISTICS & PROBABILITY
Abdallah Roubi, Mohamed Amine Mezerdi
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引用次数: 0

Abstract

Abstract We consider an infinite horizon optimal control of a system where the dynamics evolve according to a mean-field stochastic differential equation and the cost functional is also of mean-field type. These are systems where the coefficients depend not only on the state variable, but also on its marginal distribution via some linear functional. Under some concavity assumptions on the coefficients as well as on the Hamiltonian, we are able to prove a verification theorem, which gives a sufficient condition for optimality for a given admissible control. In the absence of concavity, we prove a necessary condition for optimality in the form of a weak Pontryagin maximum principle, given in terms of stationarity of the Hamiltonian.
无穷视界平均场随机微分方程最优控制的充分必要条件
摘要考虑一类系统的无限视界最优控制问题,该系统的动力学演化遵循平均场随机微分方程,其代价泛函也是平均场型。在这些系统中,系数不仅取决于状态变量,还取决于它的边际分布,通过一些线性泛函。在系数和哈密顿量的某些凹性假设下,我们证明了一个验证定理,给出了给定可容许控制的最优性的充分条件。在没有凹性的情况下,我们以弱庞特里亚金极大值原理的形式证明了最优性的一个必要条件,用哈密顿量的平稳性给出。
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来源期刊
Random Operators and Stochastic Equations
Random Operators and Stochastic Equations STATISTICS & PROBABILITY-
CiteScore
0.60
自引率
25.00%
发文量
24
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