2 research outputs found

    Optimal Blends of History and Intelligence for Robust Antiterrorism Policy

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    Abstract Antiterrorism analysis requires that security agencies blend evidence on historical patterns of terrorist behavior with incomplete intelligence on terrorist adversaries to predict possible terrorist operations and devise appropriate countermeasures. We model interactions between reactive, adaptive and intelligent adversaries embedded in minimally sufficient organizational settings to study the optimal analytic mixture, expressed as historical memory reach-back and the number of anticipatory scenarios, that should be used to design antiterrorism policy. We show that history is a valuable source of information when the terrorist organization evolves and acquires new capabilities at such a rapid pace that makes optimal strategies advocated by game-theoretic reasoning unlikely to succeed
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