Approximation algorithms for NP-hard problems
Approximation algorithms for NP-hard problems
A threshold of ln n for approximating set cover
Journal of the ACM (JACM)
The complexity of computing a Nash equilibrium
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing
Settling the Complexity of Two-Player Nash Equilibrium
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: industrial track
Computing optimal randomized resource allocations for massive security games
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
On the Complexity of Nash Equilibria and Other Fixed Points
SIAM Journal on Computing
GUARDS and PROTECT: next generation applications of security games
ACM SIGecom Exchanges
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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In recent years, algorithms for computing game-theoretic solutions have been developed for real-world security domains. These games are between a defender, who must allocate her resources to defend potential targets, and an attacker, who chooses a target to attack. Existing work has assumed the set of defender's resources to be fixed. This assumption precludes the effective use of approximation algorithms, since a slight change in the defender's allocation strategy can result in a massive change in her utility. In contrast, we consider a model where resources are obtained at a cost, initiating the study of the following optimization problem: Minimize the total cost of the purchased resources, given that every target has to be defended with at least a certain probability. We give an efficient logarithmic approximation algorithm for this problem.