Evaluating Cognitive Models and Architectures

Cognitive modeling is a promising research area combining the fields of psychology and artificial intelligence. Cognitive models have been successfully applied to different topics like theory generation in psychology, usability testing in human-computer interface research, and cognitive tutoring in algebra teaching. This paper is focused on two major problems concerning the evaluation of cognitive models and architectures. First, it is shown that current approaches to quantify model complex-ity are not sufficient and second, the claim is reinforced that the flexibility of cognitive architectures leads to the problem that they cannot be falsified and are therefore too weak to be considered as theories. Cognitive architectures From a psychologist’s point of view, the main goal of cog-nitive modeling is to simulate human cognition. A cognitive model is seen as an instantiation of a theory in a computa-tional form. This can then be used to test a certain theory empirically. Cognitive architectures like SOAR (Laird, Newell, & Rosenbloom 1987), EPIC (Kieras &Meyer 1997), and ACT