Minds and Machines 14 (4):539-549 (2004)

Authors
Jon Williamson
University of Kent
Abstract
The relationship between machine learning and the philosophy of science can be classed as a dynamic interaction: a mutually beneficial connection between two autonomous fields that changes direction over time. I discuss the nature of this interaction and give a case study highlighting interactions between research on Bayesian networks in machine learning and research on causality and probability in the philosophy of science
Keywords Computer Science   Philosophy of Mind   Artificial Intelligence   Systems Theory, Control   Interdisciplinary Studies
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DOI 10.1023/B:MIND.0000045990.57744.2b
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References found in this work BETA

Causality.Judea Pearl - 2000 - Cambridge University Press.
Causality and Explanation.Wesley C. Salmon - 1997 - Oxford University Press.
Abduction, Reason, and Science.L. Magnani - 2001 - Kluwer Academic/Plenum Publishers.

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Citations of this work BETA

A Falsificationist Account of Artificial Neural Networks.Oliver Buchholz & Eric Raidl - forthcoming - The British Journal for the Philosophy of Science.

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