The GCM model

The Generalized Context Model (GCM: Nosofsky, 1984, 1986) is an influential and empirically successful model of categorization. It is intended to explain how people make categorization decisions in a task where stimuli are presented, one at a time, over a sequence of trials, and must be classified into one of a small number of categories (usually two) based on corrective feedback.

The GCM assumes that stimuli are stored as exemplars, using their values along underlying stimulus dimensions, which correspond to points in a multidimensional psychological space. The GCM then assumes people make similarity comparisons between the current stimulus and the exemplars, and base their decision on the overall similarities to each category.

A key theoretical component of the GCM involves selective attention. The basic idea is that, to learn a category structure, people selectively attend to those dimensions of the stimuli that are relevant to distinguishing the categories. Nosofsky (1984) showed that selective attention could help explain previously puzzling empirical regularities in the ease with which people learn different category structures (Shepard, Hovland, & Jenkins, 1961).

We consider category learning data from the “Condensation B” condition reported by Kruschke (1993). This condition is shown in Figure 17.1, and involves eight stimuli—consisting of line drawings of boxes with different heights, with an interior line in different positions—divided into two groups of four, to make Category A and Category B stimuli. Kruschke (1993) collected data from 40 participants over 8 consecutive blocks of trials, within which each stimulus was presented once in a random order.