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Repeated Stackelberg security games: Learning with incomplete state information

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  • Alcantara-Jiménez, Guillermo
  • Clempner, Julio B.

Abstract

Existing applications of Stackelberg Security Games (SSGs) have make use of Reinforcement Learning (RL) approaches to learn and adapt defenders-attackers behavior. The learning process for defenders-attackers is represented by randomized strategies for the defenders applied against adversarial strategies of the attackers, which acquire feedback on their strategies observing the target that was defended-attacked. However, must of the existing SSGs RL models feature strong assumptions including that the defenders and attackers have perfect information about the behavioral model, producing inconsistencies.

Suggested Citation

  • Alcantara-Jiménez, Guillermo & Clempner, Julio B., 2020. "Repeated Stackelberg security games: Learning with incomplete state information," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    • Handle: RePEc:eee:reensy:v:195:y:2020:i:c:s0951832019304478
    DOI: 10.1016/j.ress.2019.106695
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    References listed on IDEAS

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    1. Clempner, Julio B. & Poznyak, Alexander S., 2017. "Using the extraproximal method for computing the shortest-path mixed Lyapunov equilibrium in Stackelberg security games," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 138(C), pages 14-30.
    2. Kjell Hausken, 2011. "Protecting complex infrastructures against multiple strategic attackers," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(1), pages 11-29.
    3. Zhang, Jing & Zhuang, Jun, 2019. "Modeling a multi-target attacker-defender game with multiple attack types," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 465-475.
    4. G. Quijano, Eduardo & Ríos Insua, David & Cano, Javier, 2018. "Critical networked infrastructure protection from adversaries," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 27-36.
    5. Julio B. CLEMPNER & Alexander S. POZNYAK, 2016. "Analyzing An Optimistic Attitude For The Leader Firm In Duopoly Models: A Strong Stackelberg Equilibrium Based On A Lyapunov Game Theory Approach," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(4), pages 41-60.
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    Cited by:

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