Validating a High Level Behavioral Representation Language (HERBAL): A Docking Study for ACT-R

We present a docking study for Herbal, a high-level behavioral representation language based on the problem space computational model. This study docks an ACT-R model created with Herbal to one created by hand. This comparison accomplishes several things. First, we believe such studies are necessary for achieving and demonstrating the theoretical rigor and repeatability promised by high-level representation languages. Second, it is necessary to evaluate the effectiveness and efficiency of high-level cognitive modeling languages if they are to make a significant impact in either the cognitive or social sciences. Third, this kind of study provides an opportunity to test Herbal's ability to produce ACT-R models from a GOMS-like representation that contains hierarchical methods, memory capacity, and control constructs. Finally, this study provides an example model for future validation work in this area. Our study addresses each of these points by docking Pirolli's [1] price finding model in ACT-R with the same model written in Herbal. We extended Herbal to support more memory types, and in the process may have extended the PSCM.