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A causal framework for integrating learning and reasoning

Lagnado, DA; (2009) A causal framework for integrating learning and reasoning. BEHAV BRAIN SCI , 32 (2) 211 -212. 10.1017/S0140525X09000995. Green open access

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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: Article
Title: A causal framework for integrating learning and reasoning
Open access status: An open access version is available from UCL Discovery
DOI: 10.1017/S0140525X09000995
Publisher version: http://dx.doi.org/10.1017/S0140525X09000995
Language: English
Additional information: © 2009 Cambridge University Press
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: https://discovery.ucl.ac.uk/id/eprint/149231
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