Computational Intelligence Research Group Principal investigators: Prof Andries Engelbrecht Mr Bryton Masiye Mr Nelis Franken

2 Main Research Focus  Conducts theoretical and applied research in computational intelligence  Application areas:  Optimization  Classification  Pattern recognition  Research areas:  Artificial neural networks  Swarm intelligence  Evolutionary computation  Artificial immune systems  Bioinformatics  Swarm robotics (MAS)  Data and text mining  Image analysis

3 CIRG Members  Staff members  Andries Engelbrecht, Bryton Masiye, Nelis Franken  Graduate students  PhD students: 9  Masters students: 35  B.Sc-Hons project students: 4

4 Research outputs BooksBook chapters Conference papers Journal articles Year

Graduandi  PhD students: 3  M.Sc students: 10  M.IT students: 1  M.BA students: 1  B.Sc-Hons students: 29

Funding  NRF Focus area grants  Explorative Computelligence, , R  CiClops, , R  BMW surface scanning via  Prototype, , R  Production system, , R561770

International Collaboration  With  Prof J-P Muller, CIRAD, France  Prof A Salman, University of Kuwait  Dr MGH Omran, Arab Open University, Kuwait  Visitors  Prof W Duch, Nicholaus Copernicus University, Poland  Prof J-P Muller, CIRAD, France  Prof M Wolldridge, University of Liverpool, UK

Research Detail  Artificial neural networks:  New training strategies  Model selection  Learning function derivatives  Artificial immune systems:  Analysis of overfitting  New classifier algorithms  Data clustering in changing environments

Research Detail (cont.)  Swarm Intelligence :  Particle swarm optimization : New optimization algorithms Niching to locate multiple solutions Multi-objective optimization Theoretical analysis Training game-playing agents Tracking dynamically changing objectives Constrained optimization Training support vector machines Methods for discrete search spaces

Research Detail (cont.)  Swarm intelligence (cont.):  Ant Colony Optimization: Routing in ad hoc mobile networks Foraging models for robot swarms  Swarm robotics: Social-based coordination methods Coevolutionary trained behaviours Blackboard systems

Research Detail (cont.)  Evolutionary computation:  Analysis of coevolution  Coevolutionary training of game agents  Evolving decision and model trees  New differential evolution algorithms  Bioinformatics:  DNA sequence alignment  RNA secondary structure prediction  Molecular docking

Research Detail (cont.)  Image analysis:  Surface anomaly detection  New image segmentation methods  Analysing video feeds  Gesture recognition and tracking  Data, Text, Image Mining:  Data sampling methods  Mining continuous-valued classes  Genetic programming for mining

Researc Projects  BMW surface scanning  Cilib and CiClops  CyberSaint  Scorpio  Agere  Gesture recognition, device free pointing  Counting parasitic bees  Protein visualiser

Future  Centre of Excellence in AI