The Causal and Explanatory Role of Information Stored in Connectionist Networks

Author: Haybron D.M.¹

Source: Minds and Machines, Volume 10, Number 3, August 2000 , pp. 361-380(20)

Publisher: Springer

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Abstract:

In this paper I defend the propriety of explaining the behavior of distributed connectionist networks by appeal to selected data stored therein. In particular, I argue that if there is a problem with such explanations, it is a consequence of the fact that information storage in networks is superpositional, and not because it is distributed. I then develop a ``proto-account'' of causation for networks, based on an account of Andy Clark's, that shows even superpositionality does not undermine information-based explanation. Finally, I argue that the resulting explanations are genuinely informative and not vacuous.

Keywords: connectionism; mental representation; neural networks; causation; explanation philosophy of mind

Language: English

Document Type: Regular paper

Affiliations: 1: Department of Philosophy, Rutgers University, New Brunswick, NJ 08903, USA (E-mail: haybron@ibm.net)

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