Swarm Optimization Using Agents Modeled as Distributions

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Creator: 

Bell, Nathan John

Date: 

2014

Abstract: 

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.

Subject: 

Computer Science

Language: 

English

Publisher: 

Carleton University

Thesis Degree Name: 

Master of Computer Science: 
M.C.S.

Thesis Degree Level: 

Master's

Thesis Degree Discipline: 

Computer Science

Parent Collection: 

Theses and Dissertations

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