Research

Research Areas

Nature is replete with systems that exhibit complex interactions resulting in apparently intelligent behaviour which can offer new insights into solving existing problems in the human sphere. Our research in Complex Intelligent Systems deals with modelling and understanding such systems and harnessing their power in nature-inspired algorithms for machine learning and optimisation. Accordingly some of the broad areas we deal with include evolutionary algorithms (EAs), genetic algorithms (GAs), artificial neural networks (ANNs), collective intelligence algorithms, artificial immune systems, particle swarm optimisation (PSO) and ant colony optimisation (ACO). While the algorithms and systems we develop or study are largely inspired by nature, they are not wedded to nature and can be adapted in highly artificial directions to better suit the problems one wishes to solve.

Artificial Neural Networks

Collective Intelligence, Particle Swarm Optimisation & Ant Colony Optimisation

Data Visualisation

Evolutionary Computation

Pattern Recognition