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Model-Based Reasoning in Distributed Cognitive Systems

Published online by Cambridge University Press:  01 January 2022

Nancy J. Nersessian
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Abstract

This paper examines the nature of model-based reasoning in the interplay between theory and experiment in the context of biomedical engineering research laboratories, where problem solving involves using physical models. These “model systems” are sites of experimentation where in vitro models are used to screen, control, and simulate specific aspects of in vivo phenomena. As with all models, simulation devices are idealized representations, but they are also systems themselves, possessing engineering constraints. Drawing on research in contemporary cognitive science that construes cognition as occurring in a complex distributed system comprising people and artifacts, I argue that reasoning with model systems is a constraint satisfaction process involving co-construction, manipulation, and revision of mental and physical models.

Type
Cognitive Studies of Science: Vision, Models, and Agency in Scientific Cognition
Information
Philosophy of Science , Volume 73 , Issue 5: Proceedings of the 2004 Biennial Meeting of The Philosophy of Science Association. Part II: Symposia Papers. Edited by Miriam Solomon , December 2006 , pp. 699 - 709
Copyright
Copyright © The Philosophy of Science Association

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Footnotes

‡

This research has been conducted with Wendy Newstetter (co–principal investigator), research scientists, and graduate and undergraduate students. We thank our research subjects for allowing us into their work environment and granting us numerous interviews. We gratefully acknowledge the support of the National Science Foundation ROLE Grants REC0106773 and REC0450578.

References

Barsalou, L. W. (1999), “Perceptual Symbol Systems,” Behavioral and Brain Sciences 22:577–609.CrossRefGoogle ScholarPubMed
Cartwright, N. (1983), How the Laws of Physics Lie. Oxford: Clarendon Press.CrossRefGoogle Scholar
Clark, A. (2003), Natural Born Cyborgs: Minds, Technologies, and the Future of Human Intelligence. Oxford: Oxford University Press.Google Scholar
Dennett, D. C. (2000), “Making Tools for Thinking,” in Sperber, D. (ed.), Metarepresentations: A Multidisciplinary Perspective. New York: Oxford University Press.Google Scholar
Donald, M. (1991), Origins of the Modern Mind: Three Stages in the Evolution of Culture and Cognition. Cambridge, MA: Harvard University Press.Google Scholar
Giere, R. N. (1988), Explaining Science: A Cognitive Approach. Chicago: University of Chicago Press.CrossRefGoogle Scholar
Greeno, J. G. (1998), “The Situativity of Knowing, Learning, and Research,” American Psychologist 53:5–24.CrossRefGoogle Scholar
Hesse, M. (1963), Models and Analogies in Science. London: Sheed & Ward.Google Scholar
Lakoff, G., and Johnson, M. (1998), Philosophy in the Flesh. New York: Basic Books.Google Scholar
Lave, J. (1988), Cognition in Practice: Mind, Mathematics, and Culture in Everyday Life. New York: Cambridge University Press.CrossRefGoogle Scholar
Magnani, L., Nersessian, N. J., and Thagard, P., eds. (1999), Model-Based Reasoning in Scientific Discovery. New York: Kluwer Academic Pulbishers/Plenum.CrossRefGoogle Scholar
Morgan, M. S., and Morrison, M., eds. (1999), Models as Mediators. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Nersessian, N. J. (1984), Faraday to Einstein: Constructing Meaning in Scientific Theories. Dordrecht: Martinus Nijhoff/Kluwer Academic Publishers.CrossRefGoogle Scholar
Nersessian, N. J. (1992), “How Do Scientists Think? Capturing the Dynamics of Conceptual Change in Science,” in Giere, R. (ed.), Minnesota Studies in the Philosophy of Science. Minneapolis: University of Minnesota Press.Google Scholar
Nersessian, N. J. (2002a), “The Cognitive Basis of Model-Based Reasoning in Science,” in Carruthers, P., Stich, S., and Siegal, M. (eds.), The Cognitive Basis of Science. Cambridge: Cambridge University Press.Google Scholar
Nersessian, N. J. (2002b), “Maxwell and the ‘Method of Physical Analogy': Model-Based Reasoning, Generic Abstraction, and Conceptual Change,” in Malament, D. (ed.), Reading Natural Philosophy: Essays in the History and Philosophy of Science and Mathematics. Lasalle, IL: Open Court.Google Scholar
Shore, B. (1997), Culture in Mind: Cognition, Culture and the Problem of Meaning. New York: Oxford University Press.Google Scholar
Tomasello, M. (1999), The Cultural Origins of Human Cognition. Cambridge, MA: Harvard University Press.Google Scholar