Treffer: The density classification problem for multi-states cellular automata

Title:
The density classification problem for multi-states cellular automata
Source:
Advances in artificial life (8th European conference, ECAL 2005, Canterbury, UK, September 5-9, 2005, proceedings)Lecture notes in computer science. :443-452
Publisher Information:
Berlin; New York, NY: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 14 ref 1
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Università della Calabria, 87036 Arcavacata di Rende (CS), Italy
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.17265443
Database:
PASCAL Archive

Weitere Informationen

In this paper, the results of three experiments, in which a genetic algorithm evolves one-dimensional cellular automata (CA), in order to perform the classical main task, are reported. The used systems are not elementary CA but they have a higher number of states. Our aim is to verify if the main-task results are similar to those obtained with elementary CA. Our results confirm that there is a substantial homogeneity.