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. 2018 Jul 18;8:10890. doi: 10.1038/s41598-018-29117-y

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Scalable decision-making of N-armed bandit problems. (a) Definitions of the two-, four-, eight-, 16-, 32, and 64-armed problems. The conditions are equally arranged to ensure fair comparisons. (b) CDR evolution. (c) Number of cycles necessary to reach a CDR of 0.95 as a function of N, which varies approximately as N^1.16.