Open Peer Commentary
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.
The propositional nature of human associative learning Chris J. Mitchell, Jan De Houwer and Peter F. Lovibond School of Psychology, University of New South Wales, Kensington 2052, Australia email@example.com http://www.psy.unsw.edu.au/profiles/cmitchell.html; Department of Psychology, Ghent University, Henri Dunantlaan 2, B-9000 Ghent, Belgium firstname.lastname@example.org http://users.ugent.be/~jdhouwer/">; School of Psychology, University of New South Wales, Kensington 2052, Australia email@example.com http://www.psy.unsw.edu.au/profiles/plovibond.html">