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Title: Artificial biochemical networks: a different connectionist paradigm.
Authors: MacLeod, Christopher
Capanni, Niccolo Francesco
Keywords: Artificial neural network
Protozoa
Evolutionary algorithm
Connectionism
Biochemistry
Protein
Robot
Pattern recognition
Issue Date: Feb-2010
Publisher: Springer. The original publication is available at www.springerlink.com
Citation: MACLEOD, C. and CAPANNI, N. F., 2010. Artificial biochemical networks: a different connectionist paradigm. Artificial Intelligence Review , 33 (1/2), pp. 123-134.
Abstract: Connectionist models are usually based on Artificial Neural Networks. However, there is another route towards Parallel Distributed Processing. This is by considering the origins of the intelligence displayed by the single celled organisms known as Protoctists. Such intelligence arises by means of the biochemical interactions within the animal. An artificial model of this might therefore be termed an Artificial Biochemical Network or ABN. This paper describes the attributes of such networks and illustrates their abilities in Pattern Recognition problems and in generating Time-Varying signals of a type which can be used in many control tasks. The flexibility of the system is explained using legged robots as an example. The networks are trained using Back Propagation and Evolutionary Algorithms such as Genetic Algorithms.
ISSN: 0269-2821
1573-7462
Appears in Collections:Journal articles (Engineering)

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