Work

How Collective Intelligence Emerges in a Crowd of People Through Learned Division of Labor: A Case Study

Year: 2024

Type: conference-paper

Abstract: This paper investigates the factors fostering collective intelligence (CI) through a case study of *LinVi's Experiment, where over 2000 human players collectively controll an avatar car. By conducting theoretical analysis and replicating observed behaviors through numerical simulations, we demonstrate how self-organized division of labor (DOL) among individuals fosters the emergence of CI and identify two essential conditions fostering CI by formulating this problem into a stability problem of a Markov Jump Linear System (MJLS). These conditions, independent of external stimulus, emphasize the importance of both elite and common players in fostering CI. Additionally, we propose an index for emergence of CI and a distributed method for estimating joint actions, enabling individuals to learn their optimal social roles without global action information of the whole crowd.

Source: Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics

DOI: 10.1109/smc54092.2024.10831045

Authors: Dekun Wang, Hongwei Zhang

Institution: Harbin Institute of Technology

Language: English

Topic: Distributed Control Multi-Agent Systems

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Basic and Applied Basic Research Foundation of Guangdong Province

Award: G8164723623