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arXiv 2402.14935math.OCmath.APmath.DS
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Hilbert 空间中的线性二次平均场博弈

Linear-Quadratic Mean Field Games in Hilbert spaces

Salvatore Federico, Fausto Gozzi, Daria Ghilli

AI总结:

本文首次在无限维 Hilbert 空间中发展线性二次平均场博弈理论,通过均值依赖将系统简化为 Riccati 方程与抽象发展方程的耦合系统,利用逼近程序证明解的存在唯一性,并应用于带延迟的生产规划问题。

摘要:

本文是首次尝试在可能无限维的 Hilbert 空间中发展线性二次平均场博弈理论。作为起点,我们研究了该主题大多数有限维文献中所考虑的情形,即对分布的依赖仅通过均值进入目标泛函。这一特征类似于有限维情形,允许将通常的平均场博弈系统简化为一个 Riccati 方程和一个由抽象发展方程组成的前向-后向耦合系统。该系统在无限维中是全新的,迄今尚未证明其相关结果。我们应用精细的逼近程序证明了该系统解的存在性与唯一性。我们将结果应用于控制变量存在延迟的生产产出规划问题。

英文摘要:

This paper represents the first attempt to develop a theory for linear-quadratic mean field games in possibly infinite dimensional Hilbert spaces. As a starting point, we study the case, considered in most finite dimensional contributions on the topic, where the dependence on the distribution enters just in the objective functional through the mean. This feature allows, similarly to the finite dimensional case, to reduce the usual mean field game system to a Riccati equation and a forward-backward coupled system of abstract evolution equations. Such system is completely new in infinite dimension and no results have been proved on it so far. We show existence and uniqueness of solutions for such system, applying a delicate approximation procedure. We apply the results to a production output planning problem with delay in the control variable.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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