This article presents a comprehensive survey of research concerning interactions between
associative learning and attention in humans. Four main findings are described. First …

Much recent evidence suggests some dramatic differences in the way people learn
perceptual categories, depending on exactly how the categories were constructed. Four …

Amazon Mechanical Turk (AMT) is an online crowdsourcing service where anonymous
online workers complete web-based tasks for small sums of money. The service has …

In recent years, ideas from the computational field of reinforcement learning have
revolutionized the study of learning in the brain, famously providing new, precise theories of …

Much of learning and reasoning occurs in pedagogical situations—situations in which a
person who knows a concept chooses examples for the purpose of helping a learner …

Abstract SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network)
is a model of how humans learn categories from examples. SUSTAIN initially assumes a …

The authors propose a rule-plus-exception model (RULEX) of classification learning.
According to RULEX, people learn to classify objects by forming simple logical rules and …

A complete neuroscience requires multilevel theories that address phenomena ranging from
higher-level cognitive behaviors to activities within a cell. We propose an extension to the …

This article provides an overview of the recent literature on the use of internet-based testing
to address important questions in perception research. Our goal is to provide a starting point …

Psychological theories of categorization generally focus on either rule-or exemplar-based
explanations. We present 2 experiments that show evidence of both rule induction and …