Why might a scientist want to establish a cognitive model as optimally suited to some particular environment? In this paper, I suggest that an unexamined motivation for establishing models as optimal is to uncover systematic discrepancies between idealized human behavior and observed human behavior. These discrepancies can lead to the discovery of previously unknown cognitive architecture details (e.g., resource constraints), which can then be incorporated into models and give rise to new idealized models that factor in these newly uncovered details. Further discrepancies then arise, and the process repeats itself in an iterative fashion. Most importantly, each step in this process provides evidence for descriptive claims about human cognition. The point, then, of establishing optimal models is to facilitate a particular process for marshalling evidence about the human cognitive system.
Brendan Fleig-Goldstein (Wed,) studied this question.