Playing repeated security games with multiple attacker types: a Q-iteration on a linear programming approach

This paper investigates infinite horizon repeated security games with one defender and multiple attacker types. The incomplete information brings uncertainty of attackers' behaviour for the defende...

[1]  Bo An,et al.  Multi-objective optimization for security games , 2012, AAMAS.

[2]  Abdolmajid Yolmeh,et al.  A robust approach to infrastructure security games , 2017, Comput. Ind. Eng..

[3]  Michael P. Wellman,et al.  Gradient methods for stackelberg security games , 2016, UAI 2016.

[4]  Milind Tambe,et al.  Conquering Adversary Behavioral Uncertainty in Security Games: An Efficient Modeling Robust Based Algorithm , 2016, AAAI.

[5]  Thomas A. Henzinger,et al.  Markov Decision Processes with Multiple Objectives , 2006, STACS.

[6]  Defending on networks : applying fame theory to prevent illegal activities in structured security domains , 2019 .

[7]  Bo An,et al.  An extended study on multi-objective security games , 2012, Autonomous Agents and Multi-Agent Systems.

[8]  Milind Tambe,et al.  Addressing Scalability and Robustness in Security Games with Multiple Boundedly Rational Adversaries , 2014, GameSec.

[9]  Ariel D. Procaccia,et al.  Learning to Play Stackelberg Security Games , 2015 .

[10]  Thomas Welsh Archibald,et al.  Review of Mathematical Programming Applications in Water Resource Management Under Uncertainty , 2018, Environmental Modeling & Assessment.

[11]  Bo An,et al.  PROTECT: An Application of Computational Game Theory for the Security of the Ports of the United States , 2012, AAAI.

[12]  Yevgeniy Vorobeychik,et al.  Multidefender Security Games , 2015, IEEE Intelligent Systems.

[13]  Bo An,et al.  GUARDS and PROTECT: next generation applications of security games , 2011, SECO.

[14]  Milind Tambe,et al.  TRUSTS: Scheduling Randomized Patrols for Fare Inspection in Transit Systems , 2012, IAAI.

[15]  Sheng Zhong,et al.  On repeated stackelberg security game with the cooperative human behavior model for wildlife protection , 2018, Applied Intelligence.

[16]  Andrea Castelletti,et al.  Tree-based Fitted Q-iteration for Multi-Objective Markov Decision problems , 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

[17]  Fei Fang,et al.  Green security games: apply game theory to addressing green security challenges , 2016, SECO.

[18]  H. Vincent Poor,et al.  Infrastructure security games , 2014, Eur. J. Oper. Res..

[19]  Bo An,et al.  Stackelberg Security Games: Looking Beyond a Decade of Success , 2018, IJCAI.

[20]  Marcello Restelli,et al.  Tree-based fitted Q-iteration for multi-objective Markov decision processes in water resource management , 2013 .

[21]  Pierre Geurts,et al.  Tree-Based Batch Mode Reinforcement Learning , 2005, J. Mach. Learn. Res..

[22]  Fernando Ordóñez,et al.  Risk Averse Stackelberg Security Games with Quantal Response , 2016, GameSec.

[23]  H. Vincent Poor,et al.  Incorporating Attack-Type Uncertainty Into Network Protection , 2014, IEEE Transactions on Information Forensics and Security.

[24]  Jose Emmanuel Ramirez-Marquez,et al.  Bi-objective evolutionary approach to the design of patrolling schemes for improved border security , 2017, Comput. Ind. Eng..

[25]  Milind Tambe,et al.  Stackelberg Security Games ( SSG ) Basics and Application Overview , 2018 .

[26]  Nicholas R. Jennings,et al.  Playing Repeated Security Games with No Prior Knowledge , 2016, AAMAS.

[27]  Manish Jain,et al.  Software Assistants for Randomized Patrol Planning for the LAX Airport Police and the Federal Air Marshal Service , 2010, Interfaces.

[28]  Long Tran-Thanh,et al.  Don't Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge , 2019, AAMAS.

[29]  Milind Tambe,et al.  CAPTURE: A New Predictive Anti-Poaching Tool for Wildlife Protection , 2016, AAMAS.

[30]  Milind Tambe,et al.  Comparing human behavior models in repeated Stackelberg security games: An extended study , 2016, Artif. Intell..

[31]  Sarit Kraus,et al.  An efficient heuristic approach for security against multiple adversaries , 2007, AAMAS '07.

[32]  Frans A. Oliehoek,et al.  Model-Based Reinforcement Learning under Periodical Observability , 2018, AAAI Spring Symposia.