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A cognitively based simulation of academic science

Author

Listed:
  • Isaac Naveh

    (University of Missouri)

  • Ron Sun

    (Rensselaer Polytechnic Institute)

Abstract

The models used in social simulation to date have mostly been very simplistic cognitively, with little attention paid to the details of individual cognition. This work proposes a more cognitively realistic approach to social simulation. It begins with a model created by Gilbert (1997) for capturing the growth of academic science. Gilbert’s model, which was equation-based, is replaced here by an agent-based model, with the cognitive architecture CLARION providing greater cognitive realism. Using this cognitive agent model, results comparable to previous simulations and to human data are obtained. It is found that while different cognitive settings may affect the aggregate number of scientific articles produced, they do not generally lead to different distributions of number of articles per author. The paper concludes with a discussion of the correspondence between the model and the constructivist view of academic science. It is argued that using more cognitively realistic models in simulations may lead to novel insights.

Suggested Citation

  • Isaac Naveh & Ron Sun, 2006. "A cognitively based simulation of academic science," Computational and Mathematical Organization Theory, Springer, vol. 12(4), pages 313-337, December.
    • Handle: RePEc:spr:comaot:v:12:y:2006:i:4:d:10.1007_s10588-006-8872-z
    DOI: 10.1007/s10588-006-8872-z
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    References listed on IDEAS

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    1. N. Gilbert, 1997. "A Simulation of the Structure of Academic Science," Sociological Research Online, , vol. 2(2), pages 91-105, June.
    2. Ron Sun & Isaac Naveh, 2004. "Simulating Organizational Decision-Making Using a Cognitively Realistic Agent Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 7(3), pages 1-5.
    3. Federico Cecconi & Domenico Parisi, 1998. "Individual Versus Social Survival Strategies," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(2), pages 1-1.
    4. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
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    Cited by:

    1. Brian W. Kulik & Timothy Baker, 2008. "Putting the organization back into computational organization theory: a complex Perrowian model of organizational action," Computational and Mathematical Organization Theory, Springer, vol. 14(2), pages 84-119, June.

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