DocumentCode
328416
Title
Neurite Networks: the genetic programming of cellular automata based neural nets which GROW
Author
De Garis, Hugo
Author_Institution
Brain Builder Group, ATR Human Inf. Process. Res. Labs., Kyoto, Japan
Volume
3
fYear
1993
fDate
25-29 Oct. 1993
Firstpage
2921
Abstract
This paper proposes a new branch of neural networks, called "neurite networks", it is a neural network that grows, i.e. it has an embryological component. The artificial neurite network introduced is based on a cellular automata (CA) network whose branchings are genetically programmed (i.e. they are grown under the control of a genetic algorithm). A sequence of CA signals is sent down the middle of a CA "trail". When a signal hits the end of a trail, it can make the trail extend, turn left, turn right, branch left, branch right, split, etc., depending upon the state of the CA signal. These signal sequences are treated as the chromosomes of a genetic algorithm. Once the CA network is formed, a second set of CA state transition rules is switched on to make it behave like a neural network. The fitness of this CA based neural network is measured in terms of how well it controls some behavior of a biological robot.
Keywords
cellular automata; cellular neural nets; genetic algorithms; programming; Darwin machines; GenNets; cellular automata; genetic algorithms; genetic programming; neural nets; neurite networks; Artificial neural networks; Automatic control; Biological cells; Biological control systems; Cellular neural networks; Embryo; Genetic algorithms; Genetic programming; Neural networks; Robots;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on
Print_ISBN
0-7803-1421-2
Type
conf
DOI
10.1109/IJCNN.1993.714334
Filename
714334
Link To Document