Classification errors and response times over multiple distributed sessions as a function of category structure

Premise typicality as feature inference decision-making in perceptual categories

Making property inferences for category instances is important and has been studied in two largely separate areas-categorical induction and perceptual categorization. Categorical induction has a corpus of well-established effects using complex, real-world categories; however, the representational basis of these effects is unclear. In contrast, the perceptual categorization paradigm has fostered the assessment of well-specified representation models due to its controlled stimuli and categories. In categorical induction, evaluations of premise typicality effects, stronger attribute generalization from typical category instances than from atypical, have tried to control the similarity between instances to be distinct from premise-conclusion similarity effects, stronger generalization from greater similarity. However, the extent to which similarity has been controlled is unclear for these complex stimuli. Our research embedded analogues of categorical induction effects in perceptual categories, notably premise typicality and premise conclusion similarity, in an attempt to clarify the category representation underlying feature inference. These experiments controlled similarity between instances using overlap of a small number of constrained features. Participants made inferences for test cases using displayed sets of category instances. The results showed typicality effects, premise-conclusion similarity effects, but no evidence of premise typicality effects (i.e., no preference for generalizing features from typical over atypical category instances when similarity was controlled for), with significant Bayesian support for the null. As typicality effects occurred and occur widely in the perceptual categorization paradigm, why was premise typicality absent? We discuss possible reasons. For attribute inference, is premise typicality distinct from instance similarity? These initial results suggest not.

Context, structure, and informativeness judgments: An extensive empirical investigation

We explored the nature of human informativeness judgments: namely, people's judgments about the quantity of information that object stimuli convey about the category of objects to which they belong. Informativeness judgments play a key role in everyday decision-making situations involving the selection of items from groups that best represent the "group as a whole." They also provide insight into the nature of prototype formation. We investigated informativeness judgments with an experiment involving 41 category structures - the most comprehensive and rigorous examination thus far. We assess the robustness and generalizability of the results from this experiment by examining the relationship between group-level and individual-level performance. In addition, we show that in most cases (and especially in those involving relatively lower dimensionality structures), these judgments are predicted more accurately and explained more satisfactorily by Representational Information Theory (Vigo in Information Sciences 181: 4847-4859, 2011 and in Information 4(1):1-30, 2012) and its simplest core model than by standard models of prototypicality. Finally, we argue that prototypicality models are special cases of the more general "representational information" framework.