Making Sense from Models: Modelling the Senses with Multi-net Systems

Matthew Casey
Department of Computing
University of Surrey
United Kingdom


Our understanding of both natural and artificial cognitive systems is an exciting area of research that is developing into a multi-disciplinary subject with the potential for significant impact on science, engineering and society in general. There is considerable interest in how our understanding of natural systems may help us to apply biological strategies to artificial systems, whilst there are the more traditional opportunities for using computational modelling as a tool to aid understanding of natural cognitive systems. In this talk, we will look at an example of a simple computational model of human vision built to explore categorical perception. The model successfully replicates human behaviour within a simulated set of psychophysical experiments. The work demonstrates that such simple models can give insight into how natural systems operate, whilst providing knowledge to target further human experiments. We will also relate this work to the wider context of artificial cognitive systems, including work being carried out on modelling larger brain structures such as the superior colliculus, reflecting upon the need for a paradigm shift in computational techniques, and hinting at where such a shift may come from.

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