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