This paper examines some of the constraints on cognition assumed and imposed by the ACT-R and Soar cognitive architectures. In particular, we study how these constraints either encourage or require particular types of “modeling idioms” in the form of programming patterns that commonly appear in implemented models. Because of the nature of the mapping of the architectures to human cognition, each modeling idiom translates relatively directly into changes in model behavior data, such as decision timing, memory access, and error rates. Our analysis notes that both architectures have sometimes adopted extreme and opposed constraints, where the human architecture most likely relies on some mixed or more moderate set of constraints.
Reference:
Jones, R. M., Lebiere, C., & Crossman, J. A. (2007). Comparing modeling idioms in ACT-R and Soar. Proceedings of the Eighth International Conference on Cognitive Modeling. Ann Arbor, MI.