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

Solis, Cesar U.; Clempner, Julio B.; Poznyak, Alexander S.

doi:10.14736/kyb-2019-4-0618

Cited by 5 publications

(2 citation statements)

References 36 publications

(46 reference statements)

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“…The temporal component affects the evolution of the game simply because the strategies are periodically recomputed, each time considering a static representation of the scenario. In [101], the authors propose a new model for computing effective patrol strategies in Stackelberg games, showing its efficacy on a naval simulation. It leverages the extraproximal method [102] and its extension to Markov chains, within which the unique Stackelberg/Nash equilibrium of the game is explicitly computed.…”

Section: Solving Approach Papersmentioning

confidence: 99%

Game Theory for Unmanned Vehicle Path Planning in the Marine Domain: State of the Art and New Possibilities

Cococcioni

Fiaschi

Lermusiaux

2021

JMSE

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Thanks to the advent of new technologies and higher real-time computational capabilities, the use of unmanned vehicles in the marine domain has received a significant boost in the last decade. Ocean and seabed sampling, missions in dangerous areas, and civilian security are only a few of the large number of applications which currently benefit from unmanned vehicles. One of the most actively studied topic is their full autonomy; i.e., the design of marine vehicles capable of pursuing a task while reacting to the changes of the environment without the intervention of humans, not even remotely. Environmental dynamicity may consist of variations of currents, the presence of unknown obstacles, and attacks from adversaries (e.g., pirates). To achieve autonomy in such highly dynamic uncertain conditions, many types of autonomous path planning problems need to be solved. There has thus been a commensurate number of approaches and methods to optimize this kind of path planning. This work focuses on game-theoretic approaches and provides a wide overview of the current state of the art, along with future directions.

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Section: Solving Approach Papersmentioning

confidence: 99%

Game Theory for Unmanned Vehicle Path Planning in the Marine Domain: State of the Art and New Possibilities

Cococcioni

Fiaschi

Lermusiaux

2021

JMSE

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“…Albarran and Clempner developed a solution for Stackelberg security games based in partially observable Markov games. Solis et al presented a model for computing optimal randomized security policies in Stackelberg security games for multiple players handling a Kullback‐Leibler divergence random walk for scheduling the patrol strategies.…”

Section: Introductionmentioning

confidence: 99%

Ship differential game approach for multiple players: Stackelberg security games

Solis¹,

Clempner

2019

Optim Control Appl Methods

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Casting the problem as a pursuit-evasion behavior in continuous time, this paper addresses a class of multiplayer ship differential Stackelberg security game. We are concerned with the conditions under which the defenders can capture the attackers. We represent the Stackelberg game as a Nash game for relaxing the interpretation of the noncooperative solution and the equilibrium selection problem. The weights of the players for the Nash solution are determined by their role in the Stackelberg game. The defenders try to minimize the capture condition. The attackers, knowing that they are being pursued by defenders, try to maximize the capture condition and minimize the distance to a certain target.For computing the equilibrium of the game, we employ a saddle-point method approach. The method consists of two half-steps iterated procedure where the functional of the game decrease and finally converges to an equilibrium point.We present the analysis of the convergence. Finally, we give a numerical example to illustrate the effectiveness and usefulness of our approach.

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Learning machiavellian strategies for manipulation in Stackelberg security games

Clempner

2022

Ann Math Artif Intell

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

Abstract: Institute of Mathematics of the Czech Academy of Sciences provides access to digitized documents strictly for personal use. Each copy of any part of this document must contain these Terms of use.

Cited by 5 publications

References 36 publications

Game Theory for Unmanned Vehicle Path Planning in the Marine Domain: State of the Art and New Possibilities

Game Theory for Unmanned Vehicle Path Planning in the Marine Domain: State of the Art and New Possibilities

Ship differential game approach for multiple players: Stackelberg security games

Learning machiavellian strategies for manipulation in Stackelberg security games

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