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Open Access

Research on Intelligence Evaluation Method for Crowd Collaboration System

Jinwei Miao1, Xiao Sun1, Jun Qian1, Ziyang Wang1,2, Yueting Chai1( )
National Engineering Laboratory for E-commerce Technologies, Department of Automation, Tsinghua University, Beijing 100084, China
Department of Mechanical and Electrical Engineering, Xilingol Vocational College, Xilinhot 026000, China
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Abstract

Crowd collaboration system, originating from cooperation among animals in nature, is composed of intelligent subjects, characterized by complex dynamic interactions, and has many applications in daily life. In the fields of psychology and computing, scientists have tried to quantify individual intelligence with performance on tasks. In this paper, we explore the main factors affecting group performance for small production factories from the perspective of intelligence. Based on the individual daily efficiency and the average process efficiency, we evaluate individual intelligence level and interaction intensity by integrating group size and efficiency difference, and thus propose crowd intelligence evaluation method. The rationality of the method is analyzed from overall group performance and change in the average individual performance. In the future, the intelligence evaluation method can be applied to more general production scenarios, and the impact of external uncertainty on the intelligence can be studied with simulation to achieve real-time and quantitative optimization of intelligence level of the crowd collaboration system.

Keywords

crowd collaboration systeminteraction intensityindividual intelligencecrowd intelligenceintelligence emergence

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International Journal of Crowd Science
Volume 7 Issue 3,
September 2023
Pages 120-130
DOI: 10.26599/IJCS.2023.9100008
Cite this article:
Miao J, Sun X, Qian J, et al. Research on Intelligence Evaluation Method for Crowd Collaboration System. International Journal of Crowd Science, 2023, 7(3): 120-130. https://doi.org/10.26599/IJCS.2023.9100008

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Received: 11 February 2023
Revised: 04 April 2023
Accepted: 19 April 2023
Published: 30 September 2023
© The author(s) 2023.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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