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A quantitative approach for detecting symmetries and complexity in 2D plane

A quantitative approach for detecting symmetries and complexity in 2D plane

Javaheri Javid, Mohammad Ali, Zimmer, Robert, Ursyn, Anna and Al-Rifaie, Mohammad Majid ORCID: 0000-0002-1798-9615 (2015) A quantitative approach for detecting symmetries and complexity in 2D plane. In: Theory and Practice of Natural Computing. Fourth International Conference, TPNC 2015, Mieres, Spain, December 15-16, 2015. Proceedings. Lecture Notes in Computer Science book series (LNCS), 9477 . Springer, Cham, Switzerland, pp. 150-160. ISBN 978-3319268408 ISSN 0302-9743 (Print), 1611-3349 (Online) (doi:https://doi.org/10.1007/978-3-319-26841-5_12)

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Abstract

Aesthetic evaluation of computer generated patterns is a growing filed with several challenges. This paper focuses on the quantitative evaluation of order and complexity in multi-state two-dimensional (2D) cellular automata (CA). CA are known for their ability to generate highly complex patterns through simple and well defined local interaction of rules. It is suggested that the order and complexity of 2D patterns can be quantified by using mean information gain. This measure, also known as conditional entropy, takes into account conditional and joint probabilities of the elements of a configuration in a 2D plane. A series of experiments is designed to demonstrate the effectiveness of the mean information gain in quantifying the structural order and complexity, including the orientation of symmetries of multi-state 2D CA configurations.

Item Type: Conference Proceedings
Title of Proceedings: Theory and Practice of Natural Computing. Fourth International Conference, TPNC 2015, Mieres, Spain, December 15-16, 2015. Proceedings
Uncontrolled Keywords: Symmetry complexity, entropy, information gain, cellular automata, 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 09:26
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/21006

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