A Fully Operational Framework for Handling Cellular Automata Templates

Clicks: 377
ID: 9980
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #8 of 21 articles by views in complexity

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Cellular automata are fully discrete, computational, or dynamical systems, characterised by a local, totally decentralised action. Although extremely simple in structure, they are able to represent arbitrarily complex phenomena. However, due to the very big number of rules in any nontrivial space, finding a local rule that globally unfolds as desired remains a challenging task. In order to help along this direction, here we present the current state of cellular automata templates, a data structure that allows for the representation of sets of cellular automata in a compact manner. The template data structure is defined, along with processes by which interesting templates can be built. In the end, we give an illustrative example showcasing how templates can be used to explore a very large cellular automaton space. Although the idea itself of template has been introduced before, only now its conceptual underpinnings and computational robustness rendered the notion effective for practical use.
Reference Key
mauricio2019acomplexity Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Verardo, Mauricio;de Oliveira, Pedro P. B.;Verardo, Mauricio;de Oliveira, Pedro P. B.;
Journal complexity
Year 2019
DOI
10.1155/2019/6573793
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.