A systematic methodology for cognitive modelling

摘要

The development and testing of computational models of cognition is typically ad hoc: few generally agreed methodological principles guide the process. Consequently computational models often conflate empirically justified mechanisms with pragmatic implementation details, and essential theoretical aspects of theories are frequently hard to identify. We argue that attempts to construct cognitive theories would be considerably assisted by the availability of appropriate languages for specifying cognitive models. Such languages should: (1) be syntactically clear and succinct; (2) be operationally well defined; (3) be executable; and (4) explicitly support the division between theory and implementation detail. In support of our arguments we introduce Sceptic, an executable specification language which goes some way towards satisfying these requirements. Sceptic has been successfully used to implement a number of cognitive models including Soar, and details of the Sceptic specification of Soar are included in a technical appendix. The simplicity of Sceptic Soar permits the essentials of the underlying cognitive theory to be seen, and aids investigation of alternative theoretical assumptions. We demonstrate this by reporting three computational experiments involving modifications to the functioning of working memory within Soar. Although our focus is on Soar, the thrust of the work is more concerned with general methodological issues in cognitive modelling.