Open Peer Commentary
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The proposal to recruit available formal structures to build an algorithmic model of all learning falters on close examination of its essential assumption: that the input and output of the model are propositional in structure. After giving three framework considerations, I describe three possibly fatal problems with this assumption, concluding each with a question that needs answering to avoid fatality.
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 chris.mitchell@unsw.edu.au http://www.psy.unsw.edu.au/profiles/cmitchell.html; Department of Psychology, Ghent University, Henri Dunantlaan 2, B-9000 Ghent, Belgium jan.dehouwer@ugent.be http://users.ugent.be/~jdhouwer/">; School of Psychology, University of New South Wales, Kensington 2052, Australia p.lovibond@unsw.edu.au http://www.psy.unsw.edu.au/profiles/plovibond.html">