论文标题

如何检测Salami SliCer:一款与未知比赛的随机控制器 - 杆游戏

How to detect a salami slicer: a stochastic controller-stopper game with unknown competition

论文作者

Ekström, Erik, Lindensjö, Kristoffer, Olofsson, Marcus

论文摘要

We consider a stochastic game of control and stopping specified in terms of a process $X_t=-θΛ_t+W_t$, representing the holdings of Player 1, where $W$ is a Brownian motion, $θ$ is a Bernoulli random variable indicating whether Player 2 is active or not, and $Λ$ is a non-decreasing process representing the accumulated "theft" or "fraud" performed by Player 2 (if active) against Player 1。Player1无法直接观察$θ$或$λ$,但只能观察到该过程$ x $的路径,并且可以选择“停止规则” $τ$以$ m $ $ m $。因此,玩家1不知道她是否是欺诈的受害者,并且在未知的竞争中以这种意义上的运作。玩家2可以同时观察$θ$和$ w $,并试图选择欺诈策略$λ$,从而最大程度地提高了预期的折扣金额\ [{{\ Mathbb e} \ left [θ\ int _0 _0^τe^τe^{ - rs}dλ_s\ right],\ right \ right \ right] \ \ [{\ Mathbb e} \左[θ\ int _0^τe^{ - rs}dλ_s + e^{ - rτ} m {\ mathbb i} _ {\ Mathbb i} _ {\ {τ{τ<\ inftty \ \ \}}}}}}}} \ right]。它结合了过滤(检测),非偏差控制,停止,战略特征(游戏)和不对称信息。我们为此游戏得出了纳什的平衡。对于某些参数值,我们在纯策略中找到平衡,对于其他参数值,我们通过允许随机停止策略找到平衡。

We consider a stochastic game of control and stopping specified in terms of a process $X_t=-θΛ_t+W_t$, representing the holdings of Player 1, where $W$ is a Brownian motion, $θ$ is a Bernoulli random variable indicating whether Player 2 is active or not, and $Λ$ is a non-decreasing process representing the accumulated "theft" or "fraud" performed by Player 2 (if active) against Player 1. Player 1 cannot observe $θ$ or $Λ$ directly, but can merely observe the path of the process $X$ and may choose a stopping rule $τ$ to deactivate Player 2 at a cost $M$. Player 1 thus does not know if she is the victim of fraud and operates in this sense under unknown competition. Player 2 can observe both $θ$ and $W$ and seeks to choose the fraud strategy $Λ$ that maximizes the expected discounted amount \[{\mathbb E} \left [θ\int _0^τ e^{-rs} dΛ_s \right ],\] whereas Player 1 seeks to choose the stopping strategy $τ$ so as to minimize the expected discounted cost \[{\mathbb E} \left [θ\int _0^τ e^{-rs} dΛ_s + e^{-rτ}M{\mathbb I}_{\{τ<\infty\}} \right ].\] This non-zero-sum game appears to be novel and is motivated by applications in fraud detection; it combines filtering (detection), non-singular control, stopping, strategic features (games) and asymmetric information. We derive Nash equilibria for this game; for some parameter values we find an equilibrium in pure strategies, and for other parameter values we find an equilibrium by allowing for randomized stopping strategies.

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