Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process. It is thought that humans overcome these limitations through "satisficing," fast but "good-enough" heuristic decision making that prioritizes some sources of…

People are capable of imagining and generating new category exemplars and categories. This ability has not been addressed by previous models of categorization, most of which focus on classifying category exemplars rather than generating them. We develop a formal account of exemplar and category generation which proposes that category knowledge is…

Previous research has revealed that people choose to aim toward an "optimal" endpoint when faced with a movement task with externally imposed payoffs. This optimal endpoint is modeled based on the magnitude of the payoffs and the probability of hitting the different payoff regions (endpoint variability). Endpoint selection, however, has only been…

Slippery slope arguments (SSAs) have a bad philosophical reputation. They seem, however, to be widely used and frequently accepted in many legal, political, and ethical contexts. Hahn and Oaksford (2007) argued that distinguishing strong and weak SSAs may have a rational basis in Bayesian decision theory. In this paper three experiments…

Recent cognitive research has revealed better source memory performance for familiar relative to novel stimuli. Here we consider two possible explanations for this finding. The source memory advantage for familiar stimuli could arise because stimulus novelty induces attention to stimulus features at the expense of contextual processing, resulting…

Two experiments investigated how people perform category-based induction for items that have uncertain categorization. Whereas normative considerations suggest that people should consider multiple relevant categories, much past research has argued that people focus on only the most likely category. A new method is introduced in which responses on…

Prior research suggests that preschoolers can generalize object properties based on category information conveyed by semantically-similar labels. However, previous research did not control for co-occurrence probability of labels in natural speech. The current studies re-assessed children's generalization with semantically-similar labels.…

Exemplar-similarity models such as the exemplar-based random walk (EBRW) model (Nosofsky & Palmeri, 1997b) were designed to provide a formal account of multidimensional classification choice probabilities and response times (RTs). At the same time, a recurring theme has been to use exemplar models to account for old-new item recognition and to…

We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli…

In probabilistic categorization, also known as multiple cue probability learning (MCPL), people learn to predict a discrete outcome on the basis of imperfectly valid cues. In MCPL, normatively irrelevant cues are usually ignored, which stands in apparent conflict with recent research in deterministic categorization that has shown that people…

The processes of overall similarity sorting were investigated in 5 free classification experiments. Experiments 1 and 2 demonstrated that increasing time pressure can reduce the likelihood of overall similarity categorization. Experiment 3 showed that a concurrent load also reduced overall similarity sorting. These findings suggest that overall…

The remarkable successes of the physical sciences have been built on highly general quantitative laws, which serve as the basis for understanding an enormous variety of specific physical systems. How far is it possible to construct universal principles in the cognitive sciences, in terms of which specific aspects of perception, memory, or decision…

A set of design patterns for digital item types has been developed in response to challenges identified in various projects by teachers in higher education. The goal of the projects in question was to design and develop formative and summative tests, and to develop interactive learning material in the form of quizzes. The subject domains involved…

Speeded perceptual classification experiments were conducted to distinguish among the predictions of exemplar-retrieval, decision-boundary, and prototype models. The key manipulation was that across conditions, individual stimuli received either probabilistic or deterministic category feedback. Regardless of the probabilistic feedback, however, an…

A probabilistic approach is introduced to classify and diagnose erroneous rules of operation resulting from a variety of misconceptions ("bugs") in a procedural domain of arithmetic. The model is contrasted with the deterministic approach which has commonly been used in the field of artificial intelligence, and the advantage of treating the…