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To Transform the Phenomena: Feyerabend, Proliferation, and Recurrent Neural Networks

Published online by Cambridge University Press:  01 April 2022

Paul M. Churchland
Paul M. Churchland*
Affiliation:
University of California, San Diego
*
†Department of Philosophy-0302, University of California at San Diego, La Jolla, CA 92093.
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Abstract

Paul Feyerabend recommended the methodological policy of proliferating competing theories as a means to uncovering new empirical data, and thus as a means to increase the empirical constraints that all theories must confront. Feyerabend's policy is here defended as a clear consequence of connectionist models of explanatory understanding and learning. An earlier connectionist “vindication” is criticized, and a more realistic and penetrating account is offered in terms of the computationally plastic cognitive profile displayed by neural networks with a recurrent architecture.

Information

Type
Symposium: Paul Feyerabend and His Legacy
Information
Philosophy of Science , Volume 64 , Issue S4: Supplement. Proceedings of the 1996 Biennial Meetings of the Philosophy of Science Association. Part II: Symposia Papers Dec., 1997 , 1997 , pp. S408 - S420
Copyright
Copyright © Philosophy of Science Association 1997

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Footnotes

‡

My thanks, for several helpful suggestions, to two anonymous referees.

References

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