Handling a Kullback--Leibler divergence random walk for scheduling effective patrol strategies in Stackelberg security games

Title:

Handling a Kullback--Leibler divergence random walk for scheduling effective patrol strategies in Stackelberg security games

Creator:

Solis, César U. S., Clempner, Julio B., and Poznyak, Alexander S.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:45d654a3-fc24-4581-abd9-f82afd0cf25a
uuid:45d654a3-fc24-4581-abd9-f82afd0cf25a
doi:10.14736/kyb-2019-4-0618

Subject:

Markov chains, security, Stackelberg games, and patrolling

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

This paper presents a new model for computing optimal randomized security policies in non-cooperative Stackelberg Security Games (SSGs) for multiple players. Our framework rests upon the extraproximal method and its extension to Markov chains, within which we explicitly compute the unique Stackelberg/Nash equilibrium of the game by employing the Lagrange method and introducing the Tikhonov regularization method. We also consider a game-theory realization of the problem that involves defenders and attackers performing a discrete-time random walk over a finite state space. Following the Kullback-Leibler divergence the players' actions are fixed and, then the next-state distribution is computed. The player's goal at each time step is to specify the probability distribution for the next state. We present an explicit construction of a computationally efficient strategy under mild defenders and attackers conditions and demonstrate the performance of the proposed method on a simulated target tracking problem.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

618-640

Source:

Kybernetika | 2019 Volume:55 | Number:4

Harvested from:

CDK

Metadata only:

false