Green security games: apply game theory to addressing green security challenges

In the past decade, game-theoretic applications have been successfully deployed in the real world to address security resource allocation challenges. Inspired by the success, researchers have begun focusing on applying game theory to green security domains such as protection of forests, fish, and wildlife, forming a stream of research on Green Security Games (GSGs). We provide an overview of recent advances in GSGs and list the challenges that remained open for future study.

[1]  Milind Tambe,et al.  Robust Protection of Fisheries with COmPASS , 2014, AAAI.

[2]  Milind Tambe,et al.  Optimal patrol strategy for protecting moving targets with multiple mobile resources , 2013, AAMAS.

[3]  Milind Tambe,et al.  When Security Games Go Green: Designing Defender Strategies to Prevent Poaching and Illegal Fishing , 2015, IJCAI.

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

[5]  Sarit Kraus,et al.  Deployed ARMOR protection: the application of a game theoretic model for security at the Los Angeles International Airport , 2008, AAMAS 2008.

[6]  Noa Agmon,et al.  Making the Most of Our Regrets: Regret-Based Solutions to Handle Payoff Uncertainty and Elicitation in Green Security Games , 2015, GameSec.

[7]  Bhaskar Krishnamachari,et al.  Restless Poachers: Handling Exploration-Exploitation Tradeoffs in Security Domains , 2016, AAMAS.

[8]  Milind Tambe,et al.  "A Game of Thrones": When Human Behavior Models Compete in Repeated Stackelberg Security Games , 2015, AAMAS.

[9]  Rong Yang,et al.  Adaptive resource allocation for wildlife protection against illegal poachers , 2014, AAMAS.

[10]  Milind Tambe,et al.  Security and Game Theory - Algorithms, Deployed Systems, Lessons Learned , 2011 .

[11]  Milind Tambe,et al.  Preventing Illegal Logging: Simultaneous Optimization of Resource Teams and Tactics for Security , 2016, AAAI.

[12]  Bo An,et al.  Deploying PAWS: Field Optimization of the Protection Assistant for Wildlife Security , 2016, AAAI.

[13]  Rong Yang,et al.  A robust approach to addressing human adversaries in security games , 2012, AAMAS.

[14]  Amos Azaria,et al.  Analyzing the Effectiveness of Adversary Modeling in Security Games , 2013, AAAI.

[15]  Rong Yang,et al.  Computing optimal strategy against quantal response in security games , 2012, AAMAS.

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

[17]  Milind Tambe,et al.  Learning Adversary Behavior in Security Games: A PAC Model Perspective , 2015, AAMAS.

[18]  Milind Tambe,et al.  Protecting Moving Targets with Multiple Mobile Resources , 2013, J. Artif. Intell. Res..

[19]  Milind Tambe,et al.  Three Strategies to Success: Learning Adversary Models in Security Games , 2016, IJCAI.