Simply modified GKL density classifiers that reach... - BV FAPESP
Advanced search
Start date
Betweenand
Related content
(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Simply modified GKL density classifiers that reach consensus faster

Full text
Author(s):
Mendonca, J. Ricardo G.
Total Authors: 1
Document type: Journal article
Source: Physics Letters A; v. 383, n. 19, p. 2264-2266, JUL 8 2019.
Web of Science Citations: 0
Abstract

The two-state Gacs-Kurdyumov-Levin (GKL) cellular automaton has been a staple model in the study of complex systems due to its ability to classify binary arrays of symbols according to their initial density. We show that a class of modified GKL models over extended neighborhoods, but still involving only three cells at a time, achieves comparable density classification performance but in some cases reach consensus more than twice as fast. Our results suggest the time to consensus (relative to the length of the CA) as a complementary measure of density classification performance. (C) 2019 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 17/22166-9 - Records, range, and longest increasing subsequences of random walks
Grantee:José Ricardo Gonçalves de Mendonça
Support Opportunities: Scholarships abroad - Research