ABSTRACT
The previous chapter discussed how ACT–R can model human cognition, assuming that the person has a certain set of knowledge structures with a certain set of parameters. That chapter displayed some examples of the relatively high degree of precision in the predictions of ACT–R models. For purposes of expository simplification, the examples were rather small, but later chapters display more complex models. The success of ACT–R’s performance models makes the topic of this chapter all the more compelling. How did that knowledge get in there in the first place? Performance models should be learnable.
