不完全信息多项式随机微分对策的开环纳什均衡问题

M. Jiménez-Lizárraga, M. Basin, Victoria Celeste Rodríguez Carreón, P. Rodriguez-Ramirez
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引用次数: 0

摘要

本文给出了具有不完全信息和超线性观测值的随机多项式微分对策开环纳什策略问题的近均衡解。每个玩家都有一个线性二次代价作为个人表现指标。所提出的策略设计基于所谓的状态相关里卡蒂方程,并有效地工作,如仿真示例所示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Open-loop Nash equilibrium problem in polynomial stochastic differential games with incomplete information
This paper presents a near-equilibrium solution to the problem of finding open-loop Nash strategies for a stochastic polynomial differential game with incomplete information and over linear observations. Each player has a linear-quadratic cost as the individual performance index. The proposed strategy design is based on the so-called State-Dependent Riccati Equations and works effectively as is shown in a simulation example.
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