  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 -
contrasting most of those published in the literature with periodic ones -- and
resembles several properties of pursuits observed in nature, such as the
emergent encircling or the escaper's zigzag motion.
