Short Note
Version 1
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Optima and Simplicity in Nature
Version 1
: Received: 18 August 2022 / Approved: 18 August 2022 / Online: 18 August 2022 (03:51:21 CEST)
How to cite: Dingle, K. Optima and Simplicity in Nature. Preprints 2022, 2022080330. https://doi.org/10.20944/preprints202208.0330.v1 Dingle, K. Optima and Simplicity in Nature. Preprints 2022, 2022080330. https://doi.org/10.20944/preprints202208.0330.v1
Abstract
Why are simple, regular, and symmetric shapes common in nature? Many natural shapes arise as solutions to energy minimisation or other optimisation problems, but is there a general relation between optima and simple, regular shapes and geometries? Here we argue from algorithmic information theory that for objective functions common in nature --- based on physics and engineering laws --- optimal geometries will be simple, regular, and symmetric. Further, we derive a null model prediction that if a given geometry is an optimal solution for one natural objective function, then it is a priori more likely to be optimal or close to optimal for another objective function.
Keywords
Optimisation; simplicity; Kolmogorov complexity; physics
Subject
Computer Science and Mathematics, Computer Science
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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