The causal and explanatory role of information stored in connectionist networks

Minds and Machines 10 (3):361-380 (2000)
  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 Causation  Connectionism  Explanation  Information  Logic  Representation
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