Title: Research on emergence mechanism of collective intelligence from the complexity perspective

Authors: Renbin Xiao; Zhenhui Feng; Bowen Wu

Addresses: School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China; Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China ' School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China ' School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China

Abstract: This paper explores the emergence mechanism of collective intelligence (CI) from the complexity perspective. It begins with a comparison of the main features based on the two basic stages of CI, i.e., CI 1.0 (swarm intelligence) and CI 2.0 (crowd intelligence). Considering the connection mechanism between the two stages is still unclear, we would regard higher organism group behaviours as the transition between lower organism group behaviours to crowd behaviours. Accordingly, the bionic prototypes of CI can be classified into three categories: lower organisms, higher organisms and humans. This paper first refined the emergence mechanisms of CI in lower organisms represented by labour division, i.e., stimulus-response mechanism and activation-inhibition mechanism. Subsequently, the higher organism emergence mechanism was revealed, which is the attraction-repulsion mechanism based on roles division and perception driven. Furthermore, the emergence mechanism of crowd intelligence at the perceptual level and cognitive level are presented respectively, by means of process evolutionary description based on the attraction-repulsion mechanism. Finally, the research gives a holistic illustration of the emergence mechanism of CI.

Keywords: collective intelligence; emergence; complexity; stimulus-response; activation-inhibition; attraction-repulsion; perceptual level; cognitive level.

DOI: 10.1504/IJBIC.2023.133500

International Journal of Bio-Inspired Computation, 2023 Vol.22 No.1, pp.28 - 39

Received: 08 Dec 2022
Accepted: 09 Jan 2023
Published online: 18 Sep 2023 *

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