Group chasing tactics: How to catch a faster prey

Abstract

We propose a bio-inspired, agent-based approach to describe the natural phenomenon of group chasing in both two and three dimensions. Using a set of local interaction rules we created a continuous-space and discrete-time model with time delay, external noise and limited acceleration. We implemented a unique collective chasing strategy, optimized its parameters and studied its properties when chasing a much faster, erratic escaper. We show that collective chasing strategies can significantly enhance the chasers' success rate. Our realistic approach handles group chasing within closed, soft boundaries - in contrast with the periodic ones in most published literature - and resembles several properties of pursuits observed in nature, such as emergent encircling or the escaper's zigzag motion.