ARMOR: Research on game theory for security

Submitted by on Jul 08 2014 } Suggest Revision
By: James Pita, Manish Jain, Fernando Ordez, Christopher Portway, Milind Tambe, Craig Western
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The ARMOR software casts patrolling/monitoring problems as Bayesian Stackelberg games, allowing the ARMOR program to appropriately weigh the different actions in randomization taking into account different target weights.This chapter focuses on a deployed software assistant agent that can aid police or other security agencies in randomizing their security schedules. First, the assistant must provide quality guarantees in randomization by appropriately weighing the costs and benefits of the different options available. For example, if an attack on one part of an infrastructure will cause economic damage while an attack on another could potentially cost human lives, we must weigh the two options differently giving higher weight (probability) to guarding the latter. Second, the assistant addresses the uncertainty in information that security forces have about the adversary. Third, the assistant enables a mixed-initiative interaction with potential users rather than dictating a schedule
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