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- W1879840125 abstract "Attackers' private information is one of the main issues in defensive resource allocation games in homeland security. The outcome of a defense resource allocation decision critically depends on the accuracy of estimations about the attacker's attributes. However, terrorists’ goals may be unknown to the defender, necessitating robust decisions by the defender. This article develops a robust-optimization game-theoretical model for identifying optimal defense resource allocation strategies for a rational defender facing a strategic attacker while the attacker's valuation of targets, being the most critical attribute of the attacker, is unknown but belongs to bounded distribution-free intervals. To our best knowledge, no previous research has applied robust optimization in homeland security resource allocation when uncertainty is defined in bounded distribution-free intervals. The key features of our model include (1) modeling uncertainty in attackers' attributes, where uncertainty is characterized by bounded intervals; (2) finding the robust-optimization equilibrium for the defender using concepts dealing with budget of uncertainty and price of robustness; and (3) applying the proposed model to real data." @default.
- W1879840125 created "2016-06-24" @default.
- W1879840125 creator A5077060183 @default.
- W1879840125 creator A5078851714 @default.
- W1879840125 date "2011-11-02" @default.
- W1879840125 modified "2023-10-17" @default.
- W1879840125 title "Robust Allocation of a Defensive Budget Considering an Attacker's Private Information" @default.
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- W1879840125 doi "https://doi.org/10.1111/j.1539-6924.2011.01702.x" @default.
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