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ATAL
2009
Springer

Computing optimal randomized resource allocations for massive security games

8 years 11 months ago
Computing optimal randomized resource allocations for massive security games
Predictable allocations of security resources such as police officers, canine units, or checkpoints are vulnerable to exploitation by attackers. Recent work has applied game-theoretic methods to find optimal randomized security policies, including a fielded application at the Los Angeles International Airport (LAX). This approach has promising applications in many similar domains, including police patrolling for subway and bus systems, randomized baggage screening, and scheduling for the Federal Air Marshal Service (FAMS) on commercial flights. However, the existing methods scale poorly when the security policy requires coordination of many resources, which is central to many of these potential applications. We develop new models and algorithms that scale to much more complex instances of security games. The key idea is to use a compact model of security games, which allows exponential improvements in both memory and runtime relative to the best known algorithms for solving genera...
Christopher Kiekintveld, Manish Jain, Jason Tsai,
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where ATAL
Authors Christopher Kiekintveld, Manish Jain, Jason Tsai, James Pita, Fernando Ordóñez, Milind Tambe
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