Emergent Mind

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

(1805.01987)
Published May 5, 2018 in cs.GT , cs.AI , and cs.MA

Abstract

Effective game-theoretic modeling of defender-attacker behavior is becoming increasingly important. In many domains, the defender functions not only as a player but also the designer of the game's payoff structure. 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 Lp-norm form regarding the amount of change. Focusing on problems with weighted L1-norm form 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 L0-norm form and weighted L\infty-norm form can be solved in polynomial time. We provide an extensive experimental evaluation of our proposed algorithms.

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