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Implementation of cell clustering in cellular automata

Thesis (MSc (Mathematical Sciences)) University of Stellenbosch, 2011.

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Bibliographic Details
Main Author: Adams, Roxane
Other Authors: Van Zijl, L.
Format: Thesis
Language:en_ZA
Published: Stellenbosch : University of Stellenbosch 2011
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access_status_str Open Access
author Adams, Roxane
author2 Van Zijl, L.
author_browse Adams, Roxane
Van Zijl, L.
author_facet Van Zijl, L.
Adams, Roxane
author_sort Adams, Roxane
collection Thesis
dc_rights_str_mv University of Stellenbosch
description Thesis (MSc (Mathematical Sciences)) University of Stellenbosch, 2011.
format Thesis
id oai:scholar.sun.ac.za:10019.1/6674
institution Stellenbosch University (South Africa)
language en_ZA
last_indexed 2026-06-10T12:46:49.940Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2011
publishDateRange 2011
publishDateSort 2011
publisher Stellenbosch : University of Stellenbosch
publisherStr Stellenbosch : University of Stellenbosch
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/6674 Implementation of cell clustering in cellular automata Adams, Roxane Van Zijl, L. University of Stellenbosch. Faculty of Science. Dept. of Mathematical Sciences. Dept. of Computer Science. Cell clustering Cellular automata Ca variation Dissertations -- Mathematics Theses -- Mathematics Dissertations -- Computer science Theses -- Computer science Thesis (MSc (Mathematical Sciences)) University of Stellenbosch, 2011. ENGLISH ABSTRACT: Cellular Automata (CA) have become a popular vehicle to study complex dynamical behaviour of systems. CA can be used to model a wide variety of physical, biological, chemical and other systems. Such systems typically consist of subparts that change their state independently, based on the state of their immediate surroundings and some generally shared laws of change. When the CA approach was used to solve the LEGO construction problem, the best solution was found when using a variant of CA allowing for the clustering of cells. The LEGO construction problem concerns the optimal layout of a set of LEGO bricks. The advantages found for using the CA method with clustering in this case are the ease of implementation, the significantly smaller memory usage to previously implemented methods, and its trivial extension to construct multicoloured LEGO sculptures which were previously too complex to construct. In our research we propose to explore the definitions of clustering in CA and investigate the implementation and application of this method. We look at the ant sorting method described by Lumer and Faieta, and compare the implementation of this algorithm using regular CA as well as the clustering variation. The ant sorting model is a simple model, in which ants move randomly in space and pick up and deposit objects on the basis of local information. AFRIKAANSE OPSOMMING: Sellulêre Outomate (SO) het ’n populêre metode geword om die komplekse dinamiese gedrag van sisteme bestudeer. SO kan gebruik word om ’n groot verskeidenheid fisiese, biologiese, chemiese en ander tipe sisteme te modelleer. Sulke sisteme bestaan tipies uit subafdelings wat, gebaseer op die status van hulle omgewing en ’n paar algemene gedeelde reëls van verandering, hulle status onafhanklik verander. Met die gebruik van die SO benadering om the LEGO konstruksieprobleem op te los, is die beste oplossing bereik deur gebruik te maak van ’n variant van SO, waar selle saamgroepeer kan word. Die LEGO konstruksieprobleem behels die optimale uitleg van ’n stel LEGO blokkies. In hierdie geval is die voordele van die SO met sel groepering die maklike implementasie, ’n beduidende kleiner geheuegebruik teenoor voorheen geïmplementeerde metodes, en die triviale uitbreiding daarvan om gekleurde LEGO beelde wat voorheen te kompleks was, te kan bou. In ons ondersoek verken ons die definisies van selgroepering in SO en ondersoek die implementasie en toepassing van die metode. Ons kyk na die miersorteringsmetode beskryf deur Lumer en Faieta, en vergelyk die implementasie van hierdie algoritme deur gewone SO asook die groeperingsvariasie te gebruik. Die miersorteringsmodel is ’n eenvoudige model waarin miere lukraak in ’n omgewing beweeg en voorwerpe optel of neersit volgens plaaslike inligting. 2011-02-21T18:54:40Z 2011-03-14T08:30:15Z 2011-02-21T18:54:40Z 2011-03-14T08:30:15Z 2011-03 Thesis http://hdl.handle.net/10019.1/6674 en_ZA University of Stellenbosch 73 p. : ill. application/pdf Stellenbosch : University of Stellenbosch
spellingShingle Cell clustering
Cellular automata
Ca variation
Dissertations -- Mathematics
Theses -- Mathematics
Dissertations -- Computer science
Theses -- Computer science
Adams, Roxane
Implementation of cell clustering in cellular automata
title Implementation of cell clustering in cellular automata
title_full Implementation of cell clustering in cellular automata
title_fullStr Implementation of cell clustering in cellular automata
title_full_unstemmed Implementation of cell clustering in cellular automata
title_short Implementation of cell clustering in cellular automata
title_sort implementation of cell clustering in cellular automata
topic Cell clustering
Cellular automata
Ca variation
Dissertations -- Mathematics
Theses -- Mathematics
Dissertations -- Computer science
Theses -- Computer science
url http://hdl.handle.net/10019.1/6674
work_keys_str_mv AT adamsroxane implementationofcellclusteringincellularautomata