Two-Player Diffusion Control Games with Private Information

IF 1.7 2区 数学 Q2 MATHEMATICS, APPLIED
Julian Wendt
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引用次数: 0

Abstract

This paper presents a two-player stochastic differential game with diffusion control and rewards that are zero-sum. The players have i.i.d. exponentially distributed time horizons at which their states are compared and only the best player receives a reward. We assume that players have no information about their opponent and can only use private information for controlling their state. We show that there always exists a Markovian saddle point. Moreover, we consider the existence of saddle points in the class of threshold controls, i.e., controls choosing the maximal volatility below some threshold and the minimal above. There exists a symmetric saddle point of threshold type in closed form if and only if the ratio of maximal and minimal volatility does not exceed the value \(\sqrt{2}\).

Abstract Image

具有私有信息的二人扩散控制博弈
本文提出了一个具有扩散控制和零和奖励的二人随机微分对策。玩家拥有指数分布的时间范围,他们的状态将被比较,只有最优秀的玩家才会获得奖励。我们假设玩家没有关于对手的信息,只能使用私人信息来控制自己的状态。我们证明了马尔可夫鞍点总是存在的。此外,我们考虑了一类阈值控制中鞍点的存在性,即在某一阈值以下选择最大波动率,在某一阈值以上选择最小波动率的控制。当且仅当最大波动率与最小波动率之比不超过\(\sqrt{2}\)时,存在一个封闭形式的阈值型对称鞍点。
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来源期刊
CiteScore
3.30
自引率
5.60%
发文量
103
审稿时长
>12 weeks
期刊介绍: The Applied Mathematics and Optimization Journal covers a broad range of mathematical methods in particular those that bridge with optimization and have some connection with applications. Core topics include calculus of variations, partial differential equations, stochastic control, optimization of deterministic or stochastic systems in discrete or continuous time, homogenization, control theory, mean field games, dynamic games and optimal transport. Algorithmic, data analytic, machine learning and numerical methods which support the modeling and analysis of optimization problems are encouraged. Of great interest are papers which show some novel idea in either the theory or model which include some connection with potential applications in science and engineering.
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