This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Terziyan, Vagan; Gavriushenko, Mariia; Girka, Anastasiia; Gontarenko, Andrii; Kaikova, Olena Title: Cloning and training collective intelligence with generative adversarial networks Year: 2021 Version: Published version Copyright: © 2021 The Authors. IET Collaborative Intelligent Manufacturing published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology. Rights: CC BY 4.0 Rights url: https://creativecommons.org/licenses/by/4.0/ Please cite the original version: Terziyan, V., Gavriushenko, M., Girka, A., Gontarenko, A., & Kaikova, O. (2021). Cloning and training collective intelligence with generative adversarial networks. IET Collaborative Intelligent Manufacturing, 3(1), 64-74. https://doi.org/10.1049/cim2.12008 Received: 27 April 2020 Revised: 28 October 2020 Accepted: 11 November 2020 IET Collaborative Intelligent Manufacturing DOI: 10.1049/cim2.12008 ORIGINAL RESEARCH- PAPER- - Cloning and training collective intelligence with generative adversarial networks Vagan Terziyan | Mariia Gavriushenko | Anastasiia Girka | Andrii Gontarenko | Olena Kaikova Faculty of Information technology, University of Abstract Jyväskylä, Jyväskylä, Finland Industry 4.0 and highly automated critical infrastructure can be seen as cyber‐physical‐ social systems controlled by the Collective Intelligence. Such systems are essential for the Correspondence Vagan Terziyan, Faculty of Information technology, functioning of the society and economy. On one hand, they have flexible infrastructure of University of Jyväskylä, Jyväskylä, Finland. heterogeneous systems and assets. On the other hand, they are social systems, which Email:
[email protected] include collaborating humans and artificial decision makers. Such (human plus machine) resources must be pre‐trained to perform their mission with high efficiency.