ITM Web of Conferences
Volume 3, 2014ACTIMS 2014 – Activity-Based Modeling & Simulation 2014
|Number of page(s)||9|
|Section||Intelligent and Biological Systems|
|Published online||02 December 2014|
Organisms modeling: The question of radial basis function networks
1 I3S UMR CNRS 7271, CS 40121 - 06903 Sophia-Antipolis CEDEX - France.
2 ISA UMR 7254 INRA - CNRS - Université de Nice-Sophia Antipolis, 400 route des Chappes, BP 167, 06903 Sophia Antipolis - France
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.
© Owned by the authors, published by EDP Sciences, 2014
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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