Formal Models

Abstract

This chapter introduces formal models of cognition and explains how they are similar to verbal theories but use computer programs and mathematics to avoid the many limitations of human reasoning, thereby adding precision and rigor to their explanations. The chapter discusses Marr’s (1982) levels of analyses and how information-processing systems can be understood and described in terms of the task being performed, the representations and algorithms used to perform the task, and how the latter are implemented by physical systems. This then motivates discussion of three common approaches to modeling human cognition and behavior: process models, production-system models, and connectionist models. Each of these approaches is critiqued, with discussion of its merits and limitations. The three modeling approaches are then further illustrated by showing how each might be used to explain the finding that words can be identified more efficiently if they occur in predictable sentence contexts. The chapter closes with a discussion of how cognitive models are evaluated using their simplicity, theoretical scope, compatibility (e.g., with biology), and their capacity to generate novel predictions for guiding research.