A Deployed Quantal Response-Based Patrol Planning System for the U.S. Coast Guard

Bo An, Fernando Ordóñez, Milind Tambe, Eric Shieh, Rong Yang, Craig Baldwin, Joseph DiRenzo, Kathryn Moretti, Ben Maule, G. Dale Meyer

INFORMS Journal on Applied Analytics · 2013 · 93 citations · 47 references

Concepts

Abstract

In this paper, we describe the model, theory developed, and deployment of PROTECT, a game-theoretic system that the United States Coast Guard (USCG) uses to schedule patrols in the Port of Boston. The USCG evaluated PROTECT’s deployment in the Port of Boston as a success and is currently evaluating the system in the Port of New York, with the potential for nationwide deployment. PROTECT is premised on an attacker-defender Stackelberg game model; however, its development and implementation required both theoretical contributions and detailed evaluations. We describe the work required in the deployment, which we group into five key innovations. First, we propose a compact representation of the defender’s strategy space by exploiting equivalence and dominance, to make PROTECT efficient enough to solve real-world sized problems. Second, this system does not assume that adversaries are perfectly rational, a typical assumption in previous game-theoretic models for security. Instead, PROTECT relies on a quantal response (QR) model of the adversary’s behavior. We believe this is the first real-world deployment of a QR model. Third, we develop specialized solution algorithms that can solve this problem for real-world instances and give theoretical guarantees. Fourth, our experimental results illustrate that PROTECT’s QR model handles real-world uncertainties more robustly than a perfect-rationality model. Finally, we present (1) a comparison of human-generated and PROTECT security schedules, and (2) results of an evaluation of PROTECT from an analysis by human mock attackers.

References

47