Designing the Game to Play: Optimizing Payoff Structure in Security Games

Designing the Game to Play: Optimizing Payoff Structure in Security Games

Zheyuan Ryan Shi, Ziye Tang, Long Tran-Thanh, Rohit Singh, Fei Fang

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence

We study Stackelberg Security Games where the defender, in addition to allocating defensive resources to protect targets from the attacker, can strategically manipulate the attacker’s payoff under budget constraints in weighted L^p-norm form regarding the amount of change. For the case of weighted L^1-norm constraint, we present (i) a mixed integer linear program-based algorithm with approximation guarantee; (ii) a branch-and-bound based algorithm with improved efficiency achieved by effective pruning; (iii) a polynomial time approximation scheme for a special but practical class of problems. In addition, we show that problems under budget constraints in L^0 and weighted L^\infty-norm form can be solved in polynomial time.
Keywords:
Agent-based and Multi-agent Systems: Noncooperative Games
Agent-based and Multi-agent Systems: Algorithmic Game Theory