An Evolutionary Game Theory Approach for Intelligent Patrolling

In order to achieve a secure country, many security policies and strategies have been implemented and numerous security force s have been enlisted such as regular police forces, Army, and Navy, among others. Each security force has different roles and responsibilities. One important area of concern related to national security is border security. Border protection is a chall enging problem due to the different types of illegal activity that must to be controlled such as drug smuggling, terrorist attacks, illegal immigration, etc. One common approach to achieve border security is patrolling. Patrolling can be defined as the act of traveling an area in regular intervals in order to secure it against different threats. This paper presents a hybrid method that combines an evolutionary approach and game theory concepts in order to define the multi-agent patrolling strategy that simultaneously optimizes maximum idleness, infiltration ratio, and total patrolling cost.