IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v43y2013i5p400-420.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/inte.2013.0700
    Download Restriction: no

    File URL: https://libkey.io/10.1287/inte.2013.0700?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Stahl, Dale II & Wilson, Paul W., 1994. "Experimental evidence on players' models of other players," Journal of Economic Behavior & Organization, Elsevier, vol. 25(3), pages 309-327, December.
    2. Lazar Babu, Vellara L. & Batta, Rajan & Lin, Li, 2006. "Passenger grouping under constant threat probability in an airport security system," European Journal of Operational Research, Elsevier, vol. 168(2), pages 633-644, January.
    3. McKelvey Richard D. & Palfrey Thomas R., 1995. "Quantal Response Equilibria for Normal Form Games," Games and Economic Behavior, Elsevier, vol. 10(1), pages 6-38, July.
    4. Gerald Brown & Matthew Carlyle & Douglas Diehl & Jeffrey Kline & Kevin Wood, 2005. "A Two-Sided Optimization for Theater Ballistic Missile Defense," Operations Research, INFORMS, vol. 53(5), pages 745-763, October.
    5. Gerald Brown & Matthew Carlyle & Javier Salmerón & Kevin Wood, 2006. "Defending Critical Infrastructure," Interfaces, INFORMS, vol. 36(6), pages 530-544, December.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Vicki M. Bier, 2007. "Choosing What to Protect," Risk Analysis, John Wiley & Sons, vol. 27(3), pages 607-620, June.
    8. Rogers, Brian W. & Palfrey, Thomas R. & Camerer, Colin F., 2009. "Heterogeneous quantal response equilibrium and cognitive hierarchies," Journal of Economic Theory, Elsevier, vol. 144(4), pages 1440-1467, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. Günay Uzun & Metin Dağdeviren & Mehmet Kabak, 2016. "Determining the Distribution of Coast Guard Vessels," Interfaces, INFORMS, vol. 46(4), pages 297-314, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Emmanuel Dechenaux & Dan Kovenock & Roman Sheremeta, 2015. "A survey of experimental research on contests, all-pay auctions and tournaments," Experimental Economics, Springer;Economic Science Association, vol. 18(4), pages 609-669, December.
    2. Llorente-Saguer, Aniol & Sheremeta, Roman M. & Szech, Nora, 2023. "Designing contests between heterogeneous contestants: An experimental study of tie-breaks and bid-caps in all-pay auctions," European Economic Review, Elsevier, vol. 154(C).
    3. Choo, Lawrence C.Y & Kaplan, Todd R., 2014. "Explaining Behavior in the "11-20" Game," MPRA Paper 52808, University Library of Munich, Germany.
    4. Kirman, Alan P. & Laisney, François & Pezanis-Christou, Paul, 2018. "Exploration vs exploitation, impulse balance equilibrium, and a specification test for the El Farol bar problem," ZEW Discussion Papers 18-038, ZEW - Leibniz Centre for European Economic Research.
    5. Hanaki, Nobuyuki & Koriyama, Yukio & Sutan, Angela & Willinger, Marc, 2019. "The strategic environment effect in beauty contest games," Games and Economic Behavior, Elsevier, vol. 113(C), pages 587-610.
    6. Nagel, Rosemarie & Bühren, Christoph & Frank, Björn, 2017. "Inspired and inspiring: Hervé Moulin and the discovery of the beauty contest game," Mathematical Social Sciences, Elsevier, vol. 90(C), pages 191-207.
    7. Manish Jain & Jason Tsai & James Pita & Christopher Kiekintveld & Shyamsunder Rathi & Milind Tambe & Fernando Ordóñez, 2010. "Software Assistants for Randomized Patrol Planning for the LAX Airport Police and the Federal Air Marshal Service," Interfaces, INFORMS, vol. 40(4), pages 267-290, August.
    8. Tan, Jonathan H.W. & Breitmoser, Yves & Bolle, Friedel, 2015. "Voluntary contributions by consent or dissent," Games and Economic Behavior, Elsevier, vol. 92(C), pages 106-121.
    9. Wright, James R. & Leyton-Brown, Kevin, 2017. "Predicting human behavior in unrepeated, simultaneous-move games," Games and Economic Behavior, Elsevier, vol. 106(C), pages 16-37.
    10. Holt, Charles & Kydd, Andrew & Razzolini, Laura & Sheremeta, Roman, 2014. "The Paradox of Misaligned Profiling: Theory and Experimental Evidence," MPRA Paper 56508, University Library of Munich, Germany.
    11. Breitmoser, Yves & Tan, Jonathan H.W. & Zizzo, Daniel John, 2014. "On the beliefs off the path: Equilibrium refinement due to quantal response and level-k," Games and Economic Behavior, Elsevier, vol. 86(C), pages 102-125.
    12. Alexander Matros & Wooyoung Lim & Theodore Turocy, 2009. "Raising Revenue With Raffles: Evidence from a Laboratory Experiment," Working Paper 377, Department of Economics, University of Pittsburgh, revised Feb 2009.
    13. Breitmoser, Yves, 2012. "Strategic reasoning in p-beauty contests," Games and Economic Behavior, Elsevier, vol. 75(2), pages 555-569.
    14. David L. Alderson & Gerald G. Brown & W. Matthew Carlyle, 2015. "Operational Models of Infrastructure Resilience," Risk Analysis, John Wiley & Sons, vol. 35(4), pages 562-586, April.
    15. Jacob K. Goeree & Philippos Louis, 2021. "M Equilibrium: A Theory of Beliefs and Choices in Games," American Economic Review, American Economic Association, vol. 111(12), pages 4002-4045, December.
    16. David Rios Insua & David Banks & Jesus Rios, 2016. "Modeling Opponents in Adversarial Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 36(4), pages 742-755, April.
    17. Georganas, Sotiris & Healy, Paul J. & Weber, Roberto A., 2015. "On the persistence of strategic sophistication," Journal of Economic Theory, Elsevier, vol. 159(PA), pages 369-400.
    18. Yves Breitmoser, 2021. "Controlling for presentation effects in choice," Quantitative Economics, Econometric Society, vol. 12(1), pages 251-281, January.
    19. Upravitelev, A., 2023. "Neoclassical roots of behavioral economics," Journal of the New Economic Association, New Economic Association, vol. 58(1), pages 110-140.
    20. Matthew Kovach & Gerelt Tserenjigmid, 2023. "The Focal Quantal Response Equilibrium," Papers 2304.00438, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orinte:v:43:y:2013:i:5:p:400-420. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.