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Javaheri Javid, M. A., Tim Blackwell, B., Robert, Z. and Mohammad Majid, a.-R. (2016) Analysis of information gain and Kolmogorov complexity for aesthetic evaluation of cellular automata configurations. Connection Science, 28 (2). pp. 155-170. ISSN 0954-0091
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Text (This is an Accepted Manuscript of an article published by Taylor & Francis in Connection Science on 9 March 2016, available online https://doi.org/10.1080/09540091.2016.1151861)
2016_ConnScie_IG_Kolmogorov.pdf - Accepted Version
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Abstract
Shannon entropy fails to discriminate structurally different patterns in two-dimensional images. We have adapted information gain measure and Kolmogorov complexity to overcome the shortcomings of entropy as a measure of image structure. The measures are customised to robustly quantify the complexity of images resulting from multi-state cellular automata (CA). Experiments with a two-dimensional multi-state cellular automaton demonstrate that these measures are able to predict some of the structural characteristics, symmetry and orientation of CA generated patterns.
| Publication Type: | Articles |
|---|---|
| Additional Information: | © 2016 Taylor & Francis |
| Uncontrolled Keywords: | Complexity, entropy, information gain, Kolmogorov complexity, computationalaesthetics, cellular automata |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Academic Areas > Business School |
| Depositing User: | Mohammad Ali Javaheri Javid |
| Date Deposited: | 04 Dec 2020 14:02 |
| Last Modified: | 18 Sep 2023 08:37 |
| URI: | https://eprints.chi.ac.uk/id/eprint/5547 |
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