This book examines the bottom-up applicability of swarm intelligence to solving multiple
problems such as curve fitting image segmentation and swarm robotics. It compares the
capabilities of some of the better-known bio-inspired optimization approaches especially
Particle Swarm Optimization (PSO) Darwinian Particle Swarm Optimization (DPSO) and the
recently proposed Fractional Order Darwinian Particle Swarm Optimization (FODPSO) and
comprehensively discusses their advantages and disadvantages. Further it demonstrates the
superiority and key advantages of using the FODPSO algorithm such as its ability to provide an
improved convergence towards a solution while avoiding sub-optimality. This book offers a
valuable resource for researchers in the fields of robotics sports science pattern
recognition and machine learning as well as for students of electrical engineering and
computer science.
