Long-term working memory: A computational implementation for chess expertise

Abstract

Long-term working memory (Ericsson and Kintsch, 1995) is a theory covering empirical data from several domains, including expert behaviour. One difficulty in applying and evaluating this theory, however, is that it is framed in rather general terms, and that several mechanisms and parameters are left unspecified. This paper proposes a computer implementation of the theory for a domain that Ericsson and Kintsch cover in depth, namely chess memory. Simulations of Saariluoma’s (1989) experiment where both game and random chess positions are presented auditorily make it possible to analyse two key ingredients of the theory: encoding through elaboration of LTM schemas and patterns, and encoding through retrieval structures. In the simulations, these mechanisms were modulated by two parameters. The results show that random positions, but not game positions, are sensitive to these parameters’ values.