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The Swarm Intelligence focus area is currently the most active in the group, with the largest number of members. The focus area's main interest is particle swarm optimization (PSO), with the development of new and improved PSO algorithms. Theoretical analyses of PSO are also being done, with convergence proofs being studied. Techniques are developed for constrained optimization, niching (locating multiple solutions), multi-objective optimization, dynamic optimization problems, and to cope with discrete search spaces.

Applications of PSO techniques that are under investigation include the coevolutionary training of neural networks for game playing and financial traders, scheduling, image analysis, and data clustering. The research focus area is also investigating the application of ant colony optimization techniques to exploratory data analysis, workload distribution in computer grids, energy efficient routing in mobile ad hoc networks, and network topology design.


List the current members actively doing research in this focus area. [ Show ]


L Schoeman

PhD Completed in 2010

J Grobler

PhD Started in 2009
M.Eng Completed in 2009

S Khan

PhD Completed in 2009

D Barla-Szabo

M.Sc Started in 2003
Hons-B.Sc Completed in 2002

M Neethling

M.Sc Completed in 2008

F Zablocki

M.Sc Completed in 2008

E Papacostantis

M.Sc Started in 2004
Hons-B.Sc Completed in 2003

L Messerschmidt

M.Sc Completed

C Naicker

PhD Started in 2007
M.Sc Completed in 2006
Hons-B.Sc Completed in 2002

J Conradie

Hons-B.Sc Completed in 2004

J du Plessis

M.Sc Completed in 2005

E Peer

M.Sc Completed in 2005

M Omran

PhD Completed in 2005

G Pampara

M.Sc Started in 2005
Hons-B.Sc Completed in 2004

E van Loggerenberg

M.Sc Started in 2005
Hons-B.Sc Completed in 2004

N Franken

PhD Started in 2005
M.Sc Completed in 2004
Hons-B.Sc Completed in 2002

R Brits

M.Sc Completed in 2003
Hons-B.Sc Completed in 2000

U Paquet

M.Sc Completed in 2003

F van den Bergh

PhD Completed in 2002

A Ismail

PhD Started in 2005
M.Sc Completed in 2001


List publications of this research focus area. [ Show ]



 Edwin Peer

Portrait photo




 Swarm Intelligence


 Degree specific information: M.Sc


 A Serendipitous Software Framework for Facilitating Collaboration in Computational Intelligence


A major flaw in the academic system, particularly pertaining to computer science, is that it rewards specialisation. The highly comp etitive quest for new scientific developments, or rather the quest for a better reputation and more funding, forces researchers to sp ecialise in their own fields, leaving them little time to properly explore what others are doing, sometimes even within their own field of interest. Even the peer review process, which should provide the necessary balance, fails to achieve much diversity, since reviews are typically performed by persons who are again specialists in the particular field of the work. Further, software implementations are rarely reviewed, having as a consequence the publishing of untenable results. Unfortunately, these factors contribute to an environment which is not conducive to collaboration, a cornerstone of academia building on the work of others. This work takes a step back and examines the general landscape of computational intelligence from a broad perspective, drawing on multiple disciplines to formulate a collaborative software platform, which is flexible enough to support the needs of this diverse research community. Interestingly, this project did not set out with these goals in mind, rather it evolved, over time, from something more specialised into the general framework described in this dissertation. Design patterns are studied as a means to manage the complexity of the computational intelligence paradigm in a flexible software implementation. Further, this dissertation demonstrates that releasing research software under an open source license eliminates some of the deficiencies of the academic process, while preserving, and even improving, the ability to build a reputation and pursue funding. Two software packages have been produced as products of this research: i) CILib, an open source library of computational intelligence algorithms; and ii) CiClops, which is a virtual laboratory for performing experiments that scale over multiple workstations. Together, these software packages are intended to improve the quality of research output and facilitate collaboration by sharing a rep ository of simulation data, statistical analysis tools and a single software implementation.

 Supervisor / Co-Supervisor:

 AP Engelbrecht
 F vd Bergh



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