Optimized Mutation Operator in Evolutionary Approach to Stackelberg Security Games

Abstract

In this paper, we introduce several mutation modifications in Evolutionary Algorithm for finding Strong Stackelberg Equilibrium in sequential Security Games. The mutation operator used in the state-of-the-art evolutionary method is extended with several greedy optimization techniques. Proposed mutation operators are comprehensively tested on three types of games with different characteristics (in total over 300 test games). The experimental results show that application of some of the proposed mutations yields Defender’s strategies with higher payoffs. A trade-off between the results quality and the computation time is also discussed.