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Details of Grant 

EPSRC Reference: GR/T11029/01
Title: Non-linear Media based Computers: Chemical & Neuronal Networks through Machine Learning
Principal Investigator: Bull, Professor L
Other Investigators:
Purcell, Professor W Adamatzky, Professor A Costello, Dr B
Researcher Co-Investigators:
Project Partners:
Department: Faculty of Environment and Technology
Organisation: University of the West of England
Scheme: Standard Research (Pre-FEC)
Starts: 01 December 2004 Ends: 30 November 2008 Value (£): 594,382
EPSRC Research Topic Classifications:
Biomedical neuroscience Fundamentals of Computing
Gas & Solution Phase Reactions New & Emerging Comp. Paradigms
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
GR/T11043/01 GR/T11036/01
Panel History:  
Summary on Grant Application Form
There is growing interest in research into the development of hybrid wetware-silicon devices focused on exploiting their potential for 'non-linear computing'. The aim is to harness the as yet only partially understood intricate dynamics of non-linear media to perform complex 'computations' (potentially) more effectively than with traditional architectures and to further the understanding of how such systems function. The area provides the prospect of radically new forms of machines and is enabled by improving capabilities in wetware-silicon interfacing. The research proposed here will present an approach by which networks of non-linear media - neurons and reaction-diffusion systems - can be produced to achieve a user-defined computation (or behaviour) in a way that allows control of the media used and the substrate in which they exist. Simulated evolutionary algorithms will be used to design the appropriate network structures by searching a defined space of preparation procedures to create a computing resource capable of satisfying a given objective(s).
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Organisation Website: http://www.uwe.ac.uk