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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Mobility helps problem-solving systems to avoid groupthink

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Author(s):
Gomes, Paulo F. [1, 2] ; Reia, Sandro M. [1] ; Rodrigues, Francisco A. [3, 4, 5] ; Fontanari, Jose F. [1]
Total Authors: 4
Affiliation:
[1] Univ Sao Paulo, Inst Fis Sao Carlos, Caixa Postal 369, BR-13560970 Sao Carlos, SP - Brazil
[2] Univ Fed Goias, Inst Ciencias Exatas & Tecnol, BR-75801615 Jatai, Go - Brazil
[3] Univ Warwick, Ctr Complex Sci, Coventry CV4 7AL, W Midlands - England
[4] Univ Sao Paulo, Inst Ciencias Matemat & Comp, Caixa Postal 668, BR-13560970 Sao Carlos, SP - Brazil
[5] Univ Warwick, Math Inst, Gibbet Hill Rd, Coventry CV4 7AL, W Midlands - England
Total Affiliations: 5
Document type: Journal article
Source: Physical Review E; v. 99, n. 3 MAR 6 2019.
Web of Science Citations: 1
Abstract

Groupthink occurs when everyone in a group starts thinking alike, as when people put unlimited faith in a leader. Avoiding this phenomenon is a ubiquitous challenge to problem-solving enterprises and typical countermeasures involve the mobility of group members. Here we use an agent-based model of imitative learning to study the influence of the mobility of the agents on the time they require to find the global maxima of NK-fitness landscapes. The agents cooperate by exchanging information on their fitness and use this information to copy the fittest agent in their influence neighborhoods, which are determined by face-to-face interaction networks. The influence neighborhoods are variable since the agents perform random walks in a two-dimensional space. We find that mobility is slightly harmful for solving easy problems, i.e., problems that do not exhibit suboptimal solutions or local maxima. For difficult problems, however, mobility can prevent the imitative search being trapped in suboptimal solutions and guarantees a better performance than the independent search for any system size. (AU)

FAPESP's process: 17/23288-0 - Topics on Collective Intelligence: Brainstorming, Vox Populi and Physarum polycephalum
Grantee:José Fernando Fontanari
Support Opportunities: Regular Research Grants
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:José Alberto Cuminato
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 15/17277-0 - Diffusion of Innovations: a computational approach based on Axelrod's model
Grantee:Sandro Martinelli Reia
Support Opportunities: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 16/25682-5 - Information spreading in complex networks
Grantee:Francisco Aparecido Rodrigues
Support Opportunities: Regular Research Grants