Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-18T05:02:10.012Z Has data issue: false hasContentIssue false
  • English
  • Français

How group members contribute to group performance: Evidence from agent-based simulations

Published online by Cambridge University Press:  26 October 2016

Igor Douven
Igor Douven*
Affiliation:
Sciences, normes, décision (CNRS), Paris-Sorbonne University – Maison de la Recherche, 75006 Paris, France. [email protected]://www.researchgate.net/profile/Igor_Douven
Get access Rights & Permissions [Opens in a new window]

Abstract

The authors argue that group performance depends on the degree to which group members identify with the group as well as on their degree of differentiation. In this commentary, I discuss results from agent-based simulations, suggesting that group performance depends, at least in part, on features orthogonal to agents' caring about group performance or about how they are perceived by other group members.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 39 , 2016 , e147
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Douven, I. (2010) Simulating peer disagreements. Studies in History and Philosophy of Science 41:148–57.CrossRefGoogle Scholar
Douven, I. & Riegler, A. (2010) Extending the Hegselmann-Krause model I. Logic Journal of the IGPL (Interest Group in Pure and Applied Logic) 18:323–35.Google Scholar
Douven, I. & Wenmackers, S. (in press) Inference to the best explanation versus Bayes' rule in a social setting. British Journal for the Philosophy of Science. doi: 10.1093/bjps/axv025.Google Scholar
Hegselmann, R. & Krause, U. (2002) Opinion dynamics and bounded confidence: Models, analysis, and simulations. Journal of Artificial Societies and Social Simulation 5. Available at: http://jasss.soc.surrey.ac.uk/5/3/2.html.Google Scholar
Hegselmann, R. & Krause, U. (2005) Opinion dynamics driven by various ways of averaging. Computational Economics 25:381–405.CrossRefGoogle Scholar
Hegselmann, R. & Krause, U. (2006) Truth and cognitive division of labor: First steps towards a computer aided social epistemology. Journal of Artificial Societies and Social Simulation 9. Available at: http://jasss.soc.surrey.ac.uk/9/3/10.html.Google Scholar
Hegselmann, R. & Krause, U. (2009) Deliberative exchange, truth, and cognitive division of labour: A low-resolution modeling approach. Episteme 6:130–44.CrossRefGoogle Scholar
Riegler, A. & Douven, I. (2009) Extending the Hegselmann–Krause model III: From single beliefs to complex belief states. Episteme 6:145–63.CrossRefGoogle Scholar
Wenmackers, S., Vanpoucke, D. & Douven, I. (2012) Probability of inconsistencies in theory revision. European Physical Journal B 85:1–15.CrossRefGoogle Scholar
Wenmackers, S., Vanpoucke, D. & Douven, I. (2014) Rationality: A social-epistemology perspective. Frontiers in Psychology 5:581. doi: 10.3389/fpsyg.2014.00581.CrossRefGoogle ScholarPubMed