Getting Started on a Real-World Challenge Problem in Computational Game Theory and Beyond

The goal of this paper is to introduce a real-world challenge problem for researchers in multiagent systems and beyond, where our collective efforts may have a significant impact on activities in the real-world. The challenge is in applying game theory for security: Our goal is not only to introduce the problem, but also to provide exemplars of initial successes of deployed systems in this challenge problem arena, some key open research challenges and pointers to getting started in this research.

[1]  Manish Jain,et al.  Risk-Averse Strategies for Security Games with Execution and Observational Uncertainty , 2011, AAAI.

[2]  Vincent Conitzer,et al.  Solving Stackelberg games with uncertain observability , 2011, AAMAS.

[3]  Milind Tambe,et al.  Towards Optimal Patrol Strategies for Urban Security in Transit Systems , 2011 .

[4]  Milind Tambe,et al.  Security and Game Theory: IRIS – A Tool for Strategic Security Allocation in Transportation Networks , 2011, AAMAS 2011.

[5]  Milind Tambe,et al.  A Framework for Evaluating Deployed Security Systems: Is There a Chink in your ARMOR? , 2010, Informatica.

[6]  Rong Yang,et al.  Improving Resource Allocation Strategy against Human Adversaries in Security Games , 2011, IJCAI.

[7]  Nicola Basilico,et al.  Leader-follower strategies for robotic patrolling in environments with arbitrary topologies , 2009, AAMAS.

[8]  Heidi J. Albers,et al.  Spatial modeling of extraction and enforcement in developing country protected areas , 2010 .

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

[10]  Sarit Kraus,et al.  A graph-theoretic approach to protect static and moving targets from adversaries , 2010, AAMAS.

[11]  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.

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

[13]  Vincent Conitzer,et al.  Complexity of Computing Optimal Stackelberg Strategies in Security Resource Allocation Games , 2010, AAAI.

[14]  Bo An,et al.  Mixed-Initiative Optimization in Security Games: A Preliminary Report , 2011, AAAI Spring Symposium: Help Me Help You: Bridging the Gaps in Human-Agent Collaboration.

[15]  Rong Yang,et al.  Challenges in Patrolling to Maximize Pristine Forest Area (Position Paper) , 2012, AAAI Spring Symposium: Game Theory for Security, Sustainability, and Health.

[16]  Bo An,et al.  Refinement of Strong Stackelberg Equilibria in Security Games , 2011, AAAI.

[17]  Sarit Kraus,et al.  Playing games for security: an efficient exact algorithm for solving Bayesian Stackelberg games , 2008, AAMAS.

[18]  Milind Tambe,et al.  GUARDS: game theoretic security allocation on a national scale , 2011, AAMAS.

[19]  Vincent Conitzer,et al.  A double oracle algorithm for zero-sum security games on graphs , 2011, AAMAS.

[20]  Vincent Conitzer,et al.  Security Games with Multiple Attacker Resources , 2011, IJCAI.

[21]  Jeffrey W. Herrmann Handbook of operations research for homeland security , 2013 .

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

[23]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[24]  Yevgeniy Vorobeychik,et al.  Computing Randomized Security Strategies in Networked Domains , 2011, Applied Adversarial Reasoning and Risk Modeling.

[25]  Sarit Kraus,et al.  Robust solutions to Stackelberg games: Addressing bounded rationality and limited observations in human cognition , 2010, Artif. Intell..

[26]  Milind Tambe,et al.  Approximation methods for infinite Bayesian Stackelberg games: modeling distributional payoff uncertainty , 2011, AAMAS.

[27]  R. McKelvey,et al.  Quantal Response Equilibria for Normal Form Games , 1995 .

[28]  Manish Jain,et al.  Security Games with Arbitrary Schedules: A Branch and Price Approach , 2010, AAAI.