Organisms modeling: The question of radial basis function networks - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

Organisms modeling: The question of radial basis function networks

Résumé

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 systems-theory and artificial neural networks, computer scientists are tempted to build their own systems independently of biological issues. This publication is a first-step re-evaluation of an usual machine learning technique (radial basis function(RBF) networks) in the context of systems and biological reactive organisms.
Fichier principal
Vignette du fichier
itmconf_actims2014_03002.pdf (281.67 Ko) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-01315184 , version 1 (17-05-2016)

Identifiants

Citer

Alexandre Muzy, Lauriane Massardier, Patrick Coquillard. Organisms modeling: The question of radial basis function networks. Workshop Activity-Based Modeling & Simulation (ACTIMS 2014), Centre National de la Recherche Scientifique (CNRS). FRA., Jan 2014, Zürich, Switzerland. pp.03002, ⟨10.1051/itmconf/20140303002⟩. ⟨hal-01315184⟩
84 Consultations
75 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More