An accessible introduction to the principles of computational and mathematical modeling in psychology and cognitive science This practical and readable work provides students and researchers, who are new to cognitive modeling, with the background and core knowledge they need to interpret published reports, and develop and apply models of their own. The book is structured to help readers understand the logic of individual component techniques and their relationships to each other.
An excellent intro to cognitive modeling. It masterfully curates examples of cognitive models alongside corresponding hands-on methods and code, with discussions on model comparison. I recommend it to anyone who teaches or does cognitive modeling. Note that neural networks, cognitive architecture, and bayesian modeling are very briefly discussed in the final chapter, which makes sense: each deserves its own volume(s)!
This modeling text prioritizes readability without sacrificing the knowledge of core concepts and their applications. Excellent level of engagement with the literature in modeling and existing models in psychology.