Swarm Optimization Using Agents Modeled as Distributions [thesis]

Nathan Bell
Particle Swarm Optimization (PSO) is a popular meta-heuristic for black-box optimization. Many variations and extensions of PSO have been developed since its creation in 1995, and the algorithm remains a popular topic of research. In this work we explore a new, abstracted, perspective of the PSO system and present the novel Particle Field Optimization (PFO) algorithm which harnesses this new perspective to achieve a behaviour distinct from traditional PSO systems.
doi:10.22215/etd/2014-10580 fatcat:ibfem2cdmje5hkympd5h2pyq4m