Research on Intelligence Evaluation Method for Crowd Collaboration System

Q2 Decision Sciences
Jinwei Miao;Xiao Sun;Jun Qian;Ziyang Wang;Yueting Chai
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引用次数: 0

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.
人群协作系统智能评价方法研究
群体协作系统源于自然界动物之间的协作,由智能主体组成,具有复杂的动态交互特征,在日常生活中有许多应用。在心理学和计算机领域,科学家们试图用任务表现来量化个人的智力。本文从智能的角度探讨了影响小型生产工厂团队绩效的主要因素。基于个体的日常效率和平均过程效率,通过整合群体规模和效率差异来评估个体的智力水平和互动强度,从而提出群体智力评估方法。从群体整体绩效和个体平均绩效的变化两个方面分析了该方法的合理性。未来,智能评估方法可以应用于更通用的生产场景,并可以通过仿真研究外部不确定性对智能的影响,实现人群协作系统智能水平的实时定量优化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Crowd Science
International Journal of Crowd Science Decision Sciences-Decision Sciences (miscellaneous)
CiteScore
2.70
自引率
0.00%
发文量
20
审稿时长
24 weeks
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