Five Seconds or Sixty?

The template theory presented in Gobet and Simon (1996a, 1998) is based on the EPAM theory (Feigenbaum & Simon, 1984; Richman et al., 1995), including the numerical parameters that have been estimated in tests of the latter; and it therefore offers precise predictions for the timing of cognitive processes during the presentation and recall of chess positions. This paper describes the behavior of CHREST, a computer implementation of the template theory, in a task when the presentation time is systematically varied from one second to sixty seconds, on the recall of both game and random positions, Five Seconds or Sixty? http://people.brunel.ac.uk/~hsstffg/papers/Role%20of%20Presntn%2... 2 of 28 19/05/2007 14:54 and compares the model to human data. As predicted by the model, strong players are better than weak players with both types of positions. Their superiority with random positions is especially clear with long presentation times, but is also present after brief presentation times, although smaller in absolute value. CHREST accounts for the data, both qualitatively and quantitatively. Strong players’ superiority with random positions is explained by the large number of chunks they hold in LTM. Strong players’ high recall percentage with short presentation times is explained by the presence of templates, a special class of chunks. The model is compared to other theories of chess skill, which either cannot account for the superiority of Masters with random positions (models based on high-level descriptions and on levels of processing) or predict too strong a performance of Masters with random positions (long-term working memory). Five Seconds or Sixty? Presentation Time in Expert Memory The study of expert behavior offers a unique window into human cognition. By looking at extreme performance, cognitive scientists determine what parameters of the human information-processing system can change with extensive practice, what parameters are relatively stable, and what strategies can be used to overcome the limits imposed by these stable parameters. As experts must abide by the known limits of cognition, the information gained from them can be generalized to non-experts, who, except perhaps for individual variations in the stable parameters, could become experts given enough practice and study in a domain. Ever since the seminal research of De Groot (1946/1978), expertise in chess has provided cognitive science with a wealth of empirical data and theoretical developments. Several factors explain the important role played by chess research, including: complexity of the task, which requires nearly a decade of training to reach professional level; flexibility of the chess environment, allowing many experimental manipulations; presence of a quantitative scale to rate players (the Elo rating; Elo, 1978); and cross-fertilization with research in artificial intelligence. As several of the phenomena first encountered in chess research, such as selective search, importance of pattern recognition, progressive deepening and experts' remarkable memory (Chase & Simon, 1973a, 1973b; De Groot, 1946/1978) have been found to generalize to other domains of expertise, the chess domain offers strong external validity (Charness, 1992; Gobet, 1993a). Chess research, which employs players who have spent thousand of hours practicing their art, also offers strong ecological validity. Even Neisser (1998, p. 174), who has repeatedly emphasized the importance of studying ecologically valid tasks, notes that "I have always regarded the study of chess and similar skills as part of the naturalistic study of cognition (Neisser, 1976, p. 7)." In this paper, we provide new empirical evidence about the rates at which highly expert and less expert chess players acquire information about chess positions that they observe, and how their learning rates depend on a position's resemblance to those encountered in actual games between skilled players. We show how these empirical data can be closely approximated by a computer model, CHREST, which is a variant of the EPAM model of perception and memory with memory contents relevant for chess. We believe that the phenomena we report, and the mechanisms we propose to account for them are, for the reasons mentioned above, distinctly relevant to understanding the role of expertise, not only in chess, but in other domains of human expert professional activity as well.