Many theories of learning and memory (e.g. connectionist, associative, rational, exemplar-based) produce psychological magnitude terms as output (i.e. numbers\ud representing the momentary level of some subjective property). Many theories assume that these numbers may be translated into choice probabilities via the Ratio Rule, a.k.a. the Choice Axiom (Luce, 1959) or the Constant-Ratio Rule (Clarke, 1957). We present two categorization experiments employing artificial, visual, prototype-structured stimuli constructed from twelve symbols positioned on a grid. The Ratio Rule is shown to be\ud incorrect for these experiments, given the assumption that the magnitude terms for each category are univariate functions of the number of category-appropriate symbols\ud contained in the presented stimulus. A connectionist winner-take-all model of categorical decision (Wills & McLaren, 1997) is shown to account for our data given the same\ud assumption. The central feature underlying the success of this model is the assumption that categorical decisions are based on a Thurstonian choice process (Thurstone, 1927,\ud Case V) whose noise distribution is not double exponential in form
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