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

Author

Listed:
  • Bo An

    (University of Southern California, Los Angeles, California 90089)

  • Fernando Ordóñez

    (Universidad de Chile, Santiago, RM, Chile; and University of Southern California, Los Angeles, California 90089)

  • Milind Tambe

    (University of Southern California, Los Angeles, California 90089)

  • Eric Shieh

    (University of Southern California, Los Angeles, California 90089)

  • Rong Yang

    (University of Southern California, Los Angeles, California 90089)

  • Craig Baldwin

    (United States Coast Guard, New London, Connecticut 06320)

  • Joseph DiRenzo

    (United States Coast Guard, Portsmouth, Virginia 23704)

  • Kathryn Moretti

    (United States Coast Guard, Portsmouth, Virginia 23704)

  • Ben Maule

    (United States Coast Guard, Los Angeles, California 90045)

  • Garrett Meyer

    (United States Coast Guard, Seattle, Washington 98174)

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.

Suggested Citation

  • Bo An & Fernando Ordóñez & Milind Tambe & Eric Shieh & Rong Yang & Craig Baldwin & Joseph DiRenzo & Kathryn Moretti & Ben Maule & Garrett Meyer, 2013. "A Deployed Quantal Response-Based Patrol Planning System for the U.S. Coast Guard," Interfaces, INFORMS, vol. 43(5), pages 400-420, October.
  • Handle: RePEc:inm:orinte:v:43:y:2013:i:5:p:400-420
    DOI: 10.1287/inte.2013.0700
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    References listed on IDEAS

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    Cited by:

    1. Günay Uzun & Metin Dağdeviren & Mehmet Kabak, 2016. "Determining the Distribution of Coast Guard Vessels," Interfaces, INFORMS, vol. 46(4), pages 297-314, August.
    2. Karwowski, Jan & Mańdziuk, Jacek, 2019. "A Monte Carlo Tree Search approach to finding efficient patrolling schemes on graphs," European Journal of Operational Research, Elsevier, vol. 277(1), pages 255-268.
    3. Thanh Hong Nguyen & Amulya Yadav, 2022. "A Complete Analysis on the Risk of Using Quantal Response: When Attacker Maliciously Changes Behavior under Uncertainty," Games, MDPI, vol. 13(6), pages 1-24, December.
    4. Ankur Sinha & Zhichao Lu & Kalyanmoy Deb & Pekka Malo, 2020. "Bilevel optimization based on iterative approximation of multiple mappings," Journal of Heuristics, Springer, vol. 26(2), pages 151-185, April.
    5. Hunt, Kyle & Zhuang, Jun, 2024. "A review of attacker-defender games: Current state and paths forward," European Journal of Operational Research, Elsevier, vol. 313(2), pages 401-417.
    6. Schlicher, Loe & Lurkin, Virginie, 2024. "Fighting pickpocketing using a choice-based resource allocation model," European Journal of Operational Research, Elsevier, vol. 315(2), pages 580-595.

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