An introduction to cognitive modeling

Abstract

We provide a tutorial on the basic attributes of computational cognitive models-models that are formulated as a set of mathematical equations or as a computer simulation. We first show how models can generate complex behavior and novel insights from very simple underlying assumptions about human cognition. We survey the different classes of models, from description to explanation, and present examples of each class. We then illustrate the reasons why computational models are preferable to purely verbal means of theorizing. For example, we show that computational models help theoreticians overcome the limitations of human cognition, thereby enabling us to create coherent and plausible accounts of how we think or remember and guard against subtle theoretical errors. Models can also measure latent constructs and link them to individual differences, which would escape detection if only the raw data were considered. We conclude by reviewing some open challenges.