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Spatial complexity measure for characterising cellular automata generated 2D patterns

Spatial complexity measure for characterising cellular automata generated 2D patterns

Javaheri Javid, Mohammad Ali, Blackwell, Tim, Zimmer, Robert and Al-Rifaie, Mohammad Majid ORCID: 0000-0002-1798-9615 (2015) Spatial complexity measure for characterising cellular automata generated 2D patterns. In: Progress in Artificial Intelligence. 17th Portuguese Conference on Artificial Intelligence, EPIA 2015, Coimbra, Portugal, September 8-11, 2015. Proceedings. Lecture Notes in Computer Science book series (LNCS), 9273 . Springer, Cham, Switzerland, pp. 201-212. ISBN 978-3319234854 ISSN 0302-9743 (Print), 1611-3349 (Online) (doi:https://doi.org/10.1007/978-3-319-23485-4_21)

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Abstract

Cellular automata (CA) are known for their capacity to generate complex patterns through the local interaction of rules. Often the generated patterns, especially with multi-state two-dimensional CA, can exhibit interesting emergent behaviour. This paper addresses quantitative evaluation of spatial characteristics of CA generated patterns. It is suggested that the structural characteristics of two-dimensional (2D) CA patterns can be measured using mean information gain. This information-theoretic quantity, also known as conditional entropy, takes into account conditional and joint probabilities of cell states in a 2D plane. The effectiveness of the measure is shown in a series of experiments for multi-state 2D patterns generated by CA. The results of the experiments show that the measure is capable of distinguishing the structural characteristics including symmetry and randomness of 2D CA patterns.

Item Type: Conference Proceedings
Title of Proceedings: Progress in Artificial Intelligence. 17th Portuguese Conference on Artificial Intelligence, EPIA 2015, Coimbra, Portugal, September 8-11, 2015. Proceedings
Uncontrolled Keywords: cellular automata, spatial complexity, 2D patterns
Subjects: B Philosophy. Psychology. Religion > BH Aesthetics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > Centre for Computer & Computational Science
Faculty of Liberal Arts & Sciences > School of Computing & Mathematical Sciences (CAM)
Last Modified: 20 Jul 2021 09:40
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/21013

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