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|Title: ||Temporal patterns in artificial reaction networks.|
|Authors: ||Gerrard, Claire E.|
Coghill, George M.
|Keywords: ||Artificial neural networks|
Artificial reaction networks
|Issue Date: ||Sep-2012|
|Publisher: ||Springer Verlag.|
|Citation: ||GERRARD, C., MCCALL, J., COGHILL, G. M. and MACLEOD, C., 2012. Temporal patterns in artificial reaction networks. In: A. E. P. VILLA et al (eds.) Artificial Neural Networks and Machine Learning – ICANN 2012: 22nd Annual Conference on Artificial Neural Networks. 11-14 September 2012. Berlin: Springer. Pp. 1-8.|
|Abstract: ||The Artificial Reaction Network (ARN) is a bio-inspired connection-ist paradigm based on the emerging field of Cellular Intelligence. It has proper-ties in common with both AI and Systems Biology techniques including Artifi-cial Neural Networks, Petri Nets, and S-Systems. This paper discusses the tem-poral aspects of the ARN model using robotic gaits as an example and com-pares it with properties of Artificial Neural Networks. The comparison shows that the ARN based network has similar functionality.|
|Appears in Collections:||Conference publications (Computing)|
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