There has been significant recent interest in game theoretic approaches to security, with much of the recent research focused on utilizing the leader-follower Stackelberg game model; for example, these games are at the heart of major applications such as the ARMOR program deployed for security at the LAX airport since 2007 and the IRIS program in use by the US Federal Air Marshals (FAMS). The foundational assumption for using Stackel-berg games is that security forces (leaders), acting first, commit to a randomized strategy; while their adversaries (followers) choose their best response after surveillance of this randomized strategy. Yet, in many situations, the followers may act without observation of the leader's strategy, essentially converting the game into a simultaneous-move game model. Previous work fails to address how a leader should compute her strategy given this fundamental uncertainty about the type of game faced.
Focusing on the complex games that are directly inspired by real-world security applications, the paper provides four contributions in the context of a general class of security games. First, exploiting the structure of these security games, the paper shows that the Nash equilibria in security games are interchangeable, thus alleviating the equilibrium selection problem. Second, resolving the leader's dilemma, it shows that under a natural restriction on security games, any Stackelberg strategy is also a Nash equilibrium strategy; and furthermore, the solution is unique in a class of real-world security games of which ARMOR is a key exemplar. Third, when faced with a follower that can attack multiple targets, many of these properties no longer hold. Fourth, our experimental results emphasize positive properties of games that do not fit our restrictions. Our contributions have major implications for the real-world applications.
[1]
Vincent Conitzer,et al.
Computing the optimal strategy to commit to
,
2006,
EC '06.
[2]
T. Başar,et al.
Dynamic Noncooperative Game Theory
,
1982
.
[3]
K. Bagwell.
Commitment and observability in games
,
1995
.
[4]
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.
[5]
J. Neumann,et al.
Theory of games and economic behavior
,
1945,
100 Years of Math Milestones.
[6]
Manish Jain,et al.
Computing optimal randomized resource allocations for massive security games
,
2009,
AAMAS 2009.
[7]
J. Vial,et al.
Strategically zero-sum games: The class of games whose completely mixed equilibria cannot be improved upon
,
1978
.
[8]
J. Morgan,et al.
The Value of Commitment in Contests and Tournaments When Observation is Costly
,
2004
.
[9]
Milind Tambe,et al.
Effective solutions for real-world Stackelberg games: when agents must deal with human uncertainties
,
2009,
AAMAS 2009.
[10]
Milind Tambe,et al.
Security and Game Theory: IRIS – A Tool for Strategic Security Allocation in Transportation Networks
,
2011,
AAMAS 2011.
[11]
G. Leitmann.
On generalized Stackelberg strategies
,
1978
.
[12]
Nicola Basilico,et al.
Leader-follower strategies for robotic patrolling in environments with arbitrary topologies
,
2009,
AAMAS.
[13]
E.E.C. van Damme,et al.
Games with imperfectly observable commitment
,
1997
.
[14]
B. Stengel,et al.
Leadership with commitment to mixed strategies
,
2004
.
[15]
Wieland Müller,et al.
Perfect versus Imperfect Observability - An Experimental Test of Bagwell's Result
,
2000,
Games Econ. Behav..