The Maximum Principle for Global Solutions of Stochastic Stackelberg Differential Games

A. Bensoussan, Shaokuan Chen, S. Sethi
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引用次数: 96

Abstract

For stochastic Stackelberg differential games played by a leader and a follower, there are several solution concepts in terms of the players' information sets. In this paper we derive the maximum principle for the leader's global Stackelberg solution under the adapted closed-loop memoryless information structure, where the term global signifies the leader's domination over the entire game duration. As special cases, we study linear quadratic Stackelberg games under both adapted open-loop and adapted closed-loop memoryless information structures, as well as the resulting Riccati equations.
随机Stackelberg微分对策全局解的极大原理
对于由领导者和追随者参与的随机Stackelberg微分博弈,根据参与者的信息集有几个解概念。本文导出了自适应闭环无记忆信息结构下领导者全局Stackelberg解的最大值原理,其中全局一词表示领导者在整个博弈过程中的统治。作为特殊情况,我们研究了自适应开环和自适应闭环无记忆信息结构下的线性二次型Stackelberg对策,以及由此得到的Riccati方程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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