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CIRG - Research  -  Evolutionary Computation 



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OVERVIEW

The focus of this research area is on the development of evolutionary algorithms, specifically new differential evolution algorithms, with application to dynamic environments, and coevolution. Competitive coevolution strategies in combination with particle swarm optimizers are investigated for training strategists from zero knowledge.

Applications are to solve optimization problems, game playing, data mining, and financial trading.

ACTIVE MEMBERS

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ALUMNI MEMBERS

S Khan

PhD Completed in 2009

W Duminy

M.Sc Completed in 2007

L Messerschmidt

M.Sc Completed

G Nel

M.Sc Completed in 2005

N Franken

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

G Potgieter

M.Sc Completed in 2003
Hons-B.Sc Completed in 2001

D van Wyk

M.IT Completed in 2003

GROUP PUBLICATIONS

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MEMBER PROFILE



 Name:

 Gert Nel

Portrait photo

 E-mail:

 gmn@ucs.co.za

 Group(s):

 Evolutionary Computation
 Data Mining

 

 Degree specific information: M.Sc

 Title:

 A Memetic Genetic Program for Knowledge Discovery

 Abstract:

Local search algorithms have been proved to be effective in refining solutions that have been found by other algorithms. Evolutionary algorithms, in particular global search algorithms, have shown to be successful in producing approximate solutions for optimisation and classification problems in acceptable computation times. A relatively new method, memetic algorithms, uses local search to refine the approximate solutions produced by global search algorithms. This thesis develops such a memetic algorithm. The global search algorithm used as part of the new memetic algorithm is a genetic program that implements the building block hypothesis by building simplistic decision trees representing valid solutions, and gradually increases the complexity of the trees. The specific building block hypothesis implementation is known as the building block approach to genetic programming, BGP. The effectiveness and efficiency of the new memetic algorithm, which combines the BGP algorithm with a local search algorithm, is demonstrated.

 Supervisor / Co-Supervisor:

 AP Engelbrecht

 Thesis:

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