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.