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Near-optimality conditions in mean-field control models involving continuous and impulse controls

机译:包含连续和脉冲控制的平均场控制模型中的接近最佳条件

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In this paper we discuss stochastic control models which are described by a stochastic differential equation of mean-field type, in the sense that the coefficients are permitted to depend on the state process as well as of its expected value. The control variable has two components, the first being absolutely continuous and the second is a piecewise impulse process which is not necessarily increasing. Necessary and sufficient conditions for a control to be near optimal are studied in the form of stochastic maximum principle by using Ekeland's variational principle, which allows to produce two approximate variational inequalities in integral form. The first inequality is constructed by the spike variation technique in terms of the H-function employed for absolutely continuous part of all near optimal control. The second one is defined in term of the first order adjoint process by using a convex perturbation technique for all near optimal impulse controls.
机译:在本文中,我们讨论了由均值场类型的随机微分方程描述的随机控制模型,即允许系数取决于状态过程及其预期值。控制变量有两个组成部分,第一个是绝对连续的,第二个是分段脉冲过程,不一定会增加。利用Ekeland的变分原理,以随机最大原理的形式研究了控制接近最优的充要条件,该条件允许以积分形式产生两个近似的变分不等式。第一个不等式是由尖峰变化技术根据H函数表示的,该函数用于所有接近最优控制的绝对连续部分。对于所有接近最佳的脉冲控制,通过使用凸摄动技术,根据一阶伴随过程定义第二个。

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