Abstract
This paper proposes the Multi-Operation Patrol Scheduling System (MOPSS), a new system to generate patrols for transit system. MOPSS is based on five contributions. First, MOPSS is the first system to use three fundamentally different adversary models for the threats of fare evasion, terrorism and crime, generating three significantly different types of patrol schedule. Second, to handle uncertain interruptions in the execution of patrol schedules, MOPSS uses Markov decision processes (MDPs) in its scheduling. Third, MOPSS is the first system to account for joint activities between multiple resources, by employing the well known SMART security game model that tackles coordination between defender’s resources. Fourth, we are also the first to deploy a new Opportunistic Security Game model, where the adversary, a criminal, makes opportunistic decisions on when and where to commit crimes. Our fifth, and most important, contribution is the evaluation of MOPSS via real-world deployments, providing data from security games in the field.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
References
Bland, M.J., Kerry, S.M.: Weighted comparison of means. BMJ: British Medical Journal 316, 125–129 (1998)
Brantingham, P., Brantingham, P.: Criminality of place. European Journal on Criminal Policy and Research (1995)
Brown, A., Camerer, C.F., Lovallo, D.: To review or not to review? limited strategic thinking at the movie box office. American Economic Journal: Microeconomics 2 (2012)
Brown, M., An, B., Kiekintveld, C., Ordonez, F., Tambe, M.: An extended study on multi-objective security games. JAAMAS (2013)
Conitzer, V.: Computing game-theoretic solutions and applications to security. In: AAAI (2012)
Gatti, N.: Game theoretical insights in strategic patrolling: Model and algorithm in normal form. In: ECAI (2008)
Lisa, R., Goldberg, A.N.: Kercheval, and Kiseop Lee. t-statistics for weighted means in credit risk modeling. Journal of Risk Finance 6(4), 349–365 (2005)
Jaulmes, R., Pineau, J., Precup, D.: A formal framework for robot learning and control under model uncertainty. In: ICRA (2007)
Jiang, A.X., Yin, Z., Zhang, C., Tambe, M., Kraus, S.: Game-theoretic randomization for security patrolling with dynamic execution uncertainty. In: AAMAS (2013)
Kiekintveld, C., Jain, M., Tsai, J., Pita, J., Ordez, F., Tambe, M.: Computing optimal randomized resource allocations for massive security games. In: AAMAS, pp. 233–239 (2009)
Luber, S., Yin, Z., Delle Fave, F.M., Jiang, A.X., Tambe, M., Sullivan, J.P.: Game-theoretic patrol strategies for transit systems: The trusts system and its mobile app (demonstration). In: AAMAS (Demonstrations Track) (2013)
Ostling, R., Wang, J., Tao-yi, J., Chou, E.Y., Camerer, C.F.: Testing game theory in the field: Swedish lupi lottery games. American Economic Journal: Microeconomics (2011)
Shieh, E., An, B., Yang, R., Tambe, M., Baldwin, C., Di Renzo, J., Maule, B., Meyer, G.: Protect: A deployed game theoretic system to protect the ports of the united states. In: AAMAS (2012)
Shieh, E., Jain, M., Jiang, A.X., Tambe, M.: Effciently solving joint activity based security games. In: IJCAI (2013)
Short, M.B., D’Orsogna, M.R., Pasour, V.B., Tita, G.E., Brantingham, P.J., Bertozzi, A.L., Chayes, L.B.: A statistical model of criminal behavior. Mathematical Models and Methods in Applied Sciences (2008)
Tambe, M.: Security and Game Theory: Algorithms, Deployed Systems, Lessons Learned. Cambridge University Press (2011)
Varakantham, P., Lau, H.C., Yuan, Z.: Scalable randomized patrolling for securing rapid transit networks. In: IAAI (2013)
Yin, Z., Jiang, A., Johnson, M., Tambe, M., Kiekintveld, C., Leyton-Brown, K., Sandholm, T., Sullivan, J.: Trusts: Scheduling randomized patrols for fare inspection in transit systems. In: IAAI (2012)
Yin, Z., Tambe, M.: A unified method for handling discrete and continuous uncertainty in Bayesian stackelberg games. In: International Conference on Autonomous Agents and Multiagent Systems (AAMAS) (2012)
Zhang, C., Jiang, A.X., Short, M.B., Brantingham, J.P., Tambe, M.: Towards a game theoretic approach for defendingagainst crime diffusion. In: AAMAS (2014)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Fave, F.M.D. et al. (2014). Security Games in the Field: Deployments on a Transit System. In: Dalpiaz, F., Dix, J., van Riemsdijk, M.B. (eds) Engineering Multi-Agent Systems. EMAS 2014. Lecture Notes in Computer Science(), vol 8758. Springer, Cham. https://doi.org/10.1007/978-3-319-14484-9_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-14484-9_6
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14483-2
Online ISBN: 978-3-319-14484-9
eBook Packages: Computer ScienceComputer Science (R0)