A two-resource allocation algorithm with an application to large-scale zero-sum defensive games

Golany, Boaz; Goldberg, Noam; Rothblum, Uriel G.

doi:10.1016/j.cor.2016.08.013

Cited by 22 publications

(14 citation statements)

References 21 publications

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“…To date, many researchers have addressed the attacker‐defender game, where each player seeks to maximize a single objective function under certain constraints. Game theory and the concept of Nash equilibrium have been recognized as suitable tools for studying such strategy‐interaction resource allocation problems for a long time . For example, Zhuang and Bier utilized game theory to identify the best defensive strategy with endogenous attacker effort for countering terrorism and natural disasters.…”

Section: Introductionmentioning

confidence: 99%

“…Game theory and the concept of Nash equilibrium have been recognized as suitable tools for studying such strategy-interaction resource allocation problems for a long time. [4][5][6] For example, Zhuang and Bier 7 utilized game theory to identify the best defensive strategy with endogenous attacker effort for countering terrorism and natural disasters. Bier et al 8 explored a rigorous computational model for the optimal allocation of resources among potential terrorist targets.…”

Section: Introductionmentioning

confidence: 99%

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A game‐theoretic model for resource allocation with deception and defense efforts

Zhang

Hipel

et al. 2019

Systems Engineering

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This paper develops a strategy for assisting two players in allocating multiple resources in a strategic sequential game. The defender first needs to allocate deception and defense efforts among targets to deceive the attacker and strengthen the target, respectively. Then, the attacker chooses a type of threat and a target to attack. The defender aims at mitigating the possible damage to the targets, whereas the attacker strives to cause maximum damage to the targets. Traditional modeling approaches typically focus only on the defender's homogeneous resource in defense and are not well suited to effectively capture the complex interplay between players. Given scarce resources, a game‐theoretic model is proposed for determining optimal strategies for both players. The key novel features of this model include: (1) the attacker's learning and the defender's counter‐learning efforts are considered; (2) trade‐offs between deception and defense efforts among different targets for the defender are investigated; and (3) sensitive analysis is carried out to see how different parameters can affect the equilibrium results. An illustrative example is presented to demonstrate the procedure of this game‐theoretic model and show its effectiveness. The results can provide additional insights for defense and deception strategies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A game‐theoretic model for resource allocation with deception and defense efforts

Zhang

Hipel

et al. 2019

Systems Engineering

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“…Allocating resources by optimising an objective function, in particular, a linear one is one of the classic problems in operations research which can be traced back to the foundation of linear programming [26, 27]. Studying this problem by classic approaches gives a static, fix results.…”

Section: Introductionmentioning

confidence: 99%

Stable multi‐player evolutionary game for two‐choice resource allocation problems

Naghavi

Kebriaei

Shah-Mansouri

2019

IET Control Theory & Applications

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“…1, if B s new operation loops can cover R s threat nodes 0, if B s new operation loops can not cover R s threat nodes (11) In summary, the cumulative threat (D B ) expression is:…”

Section: Evaluation Of Threat Reduction Effectsmentioning

confidence: 99%

Operation Loop-Based Optimization Model for Resource Allocation to Military Countermeasures versus Probabilistic Threat

et al. 2018

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Weapons development planning is an unstructured and complex multi-criteria decisionmaking problem, especially in antagonistic environments. In this paper, the defender's decision was modelled as a high complexity non-linear optimization problem with limited resources. An operation loop with realistic link rules was first proposed to model the cooperation relationships among weapons in the defense system. The system dynamics principle was used to characterize the dynamic behavior of the nodes in a complex weapons network. Then, we used cumulative threat and development risk to measure different planning solutions by considering the opponent and uncertainties in the development process. Next, an improved Differential Evolution (DE) and Non-Dominated Sorting Differential Evolution (NSDE) were designed to determine the optimal planning solutions for a single objective and multi-objective. The compromise solution, based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), was used to evaluate the Pareto solution set of the multi-objective. Finally, an illustrative case was studied to verify the feasibility and validity of the proposed model.

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A two-resource allocation algorithm with an application to large-scale zero-sum defensive games

Cited by 22 publications

References 21 publications

A game‐theoretic model for resource allocation with deception and defense efforts

A game‐theoretic model for resource allocation with deception and defense efforts

Stable multi‐player evolutionary game for two‐choice resource allocation problems

Operation Loop-Based Optimization Model for Resource Allocation to Military Countermeasures versus Probabilistic Threat

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