Date of Original Version

2-2015

Type

Working Paper

Abstract or Description

Game-theoretic algorithms for the protection of critical infrastructure sites have been widely deployed in recent years. Important sites are protected by multiple agencies that assign their resources almost independently; but limited coordination has been shown to result in significant inefficiencies. Encouraging the agencies to coordinate requires developing mechanisms that can assign their resources simultaneously while sharing a minimal amount of sensitive information across agencies. We draw on the Alternating Direction Method of Multipliers (ADMM) — a distributed convex optimization method that plays a key role in machine learning research — to develop such coordination mechanisms for two agencies with provably optimal efficiency

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