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A causal framework for integrating learning and reasoning

Published online by Cambridge University Press:  23 April 2009

David A. Lagnado
David A. Lagnado
Affiliation:
Department of Cognitive, Perceptual, and Brain Sciences, University College London, London WC1E 6BT, United [email protected]://www.psychol.ucl.ac.uk/people/profiles/lagnado_david.htm
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Abstract

Can the phenomena of associative learning be replaced wholesale by a propositional reasoning system? Mitchell et al. make a strong case against an automatic, unconscious, and encapsulated associative system. However, their propositional account fails to distinguish inferences based on actions from those based on observation. Causal Bayes networks remedy this shortcoming, and also provide an overarching framework for both learning and reasoning. On this account, causal representations are primary, but associative learning processes are not excluded a priori.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 32 , Issue 2 , April 2009 , pp. 211 - 212
Copyright
Copyright © Cambridge University Press 2009

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