Organisms modeling: The question of radial basis function networks

Organisms modeling: The question of radial basis function networks

There exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of system-theory and artifical neural networks, computer scientists are tempted to build their own systems independentl...

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Main Authors: Muzy Alexandre, Massardier Lauriane, Coquillard Patrick
Format: Article
Language:English
Published: EDP Sciences 2014-01-01
Series:ITM Web of Conferences
Online Access:http://dx.doi.org/10.1051/itmconf/20140303002
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spelling doaj-76800a56d913478fa448d087a52116372021-02-02T01:27:18ZengEDP SciencesITM Web of Conferences2271-20972014-01-0130300210.1051/itmconf/20140303002itmconf_actims2014_03002Organisms modeling: The question of radial basis function networksMuzy Alexandre0Massardier Lauriane1Coquillard Patrick2I3S UMR CNRS 7271ISA UMR 7254 INRA - CNRS - Université de Nice-Sophia AntipolisISA UMR 7254 INRA - CNRS - Université de Nice-Sophia Antipolis There exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of system-theory and artifical neural networks, computer scientists are tempted to build their own systems independently of biological issues. This publication is a first-step re-evalution of an usual machine learning technique (radial basis funtion(RBF) networks) in the context of systems and biological reactive organisms. http://dx.doi.org/10.1051/itmconf/20140303002
collection DOAJ
language English
format Article
sources DOAJ
author Muzy Alexandre
Massardier Lauriane
Coquillard Patrick
spellingShingle Muzy Alexandre
Massardier Lauriane
Coquillard Patrick
Organisms modeling: The question of radial basis function networks
ITM Web of Conferences
author_facet Muzy Alexandre
Massardier Lauriane
Coquillard Patrick
author_sort Muzy Alexandre
title Organisms modeling: The question of radial basis function networks
title_short Organisms modeling: The question of radial basis function networks
title_full Organisms modeling: The question of radial basis function networks
title_fullStr Organisms modeling: The question of radial basis function networks
title_full_unstemmed Organisms modeling: The question of radial basis function networks
title_sort organisms modeling: the question of radial basis function networks
publisher EDP Sciences
series ITM Web of Conferences
issn 2271-2097
publishDate 2014-01-01
description There exists usually a gap between bio-inspired computational techniques and what biologists can do with these techniques in their current researches. Although biology is the root of system-theory and artifical neural networks, computer scientists are tempted to build their own systems independently of biological issues. This publication is a first-step re-evalution of an usual machine learning technique (radial basis funtion(RBF) networks) in the context of systems and biological reactive organisms.
url http://dx.doi.org/10.1051/itmconf/20140303002
work_keys_str_mv AT muzyalexandre organismsmodelingthequestionofradialbasisfunctionnetworks
AT massardierlauriane organismsmodelingthequestionofradialbasisfunctionnetworks
AT coquillardpatrick organismsmodelingthequestionofradialbasisfunctionnetworks
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