Memory for the meaningless: How chunks help

It is a classic result in cognitive science that chess masters can recall briefly presented positions better than weaker players when these positions are meaningful, but that their superiority disappears with random positions. However, Gobet and Simon (1996a) have recently shown that there is a skill effect with random chess positions as well. The impact of this result for theories of expert memory is discussed. CHREST, a computational, chunking model of chess expertise based on EPAM (Feigenbaum & Simon, 1984) accounts for this skill difference. The model is also compared with human data from an experiment where the role of presentation time for random positions was systematically varied from 1 second to 60 seconds. Simulations show that the model captures the main features of the human data, thus adding support to the EPAM theory. They also corroborate earlier estimates that visual short-term memory may contain three or four chunks

Five seconds or sixty? Presentation time in expert memory

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, 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)

A pattern-recognition theory of search in expert problem solving

Understanding how look-ahead search and pattern recognition interact is one of the important research questions in the study of expert problem-solving. This paper examines the implications of the template theory (Gobet & Simon, 1996a), a recent theory of expert memory, on the theory of problem solving in chess. Templates are "chunks" (Chase & Simon, 1973) that have evolved into more complex data structures and that possess slots allowing values to be encoded rapidly. Templates may facilitate search in three ways: (a) by allowing information to be stored into LTM rapidly; (b) by allowing a search in the template space in addition to a search in the move space; and (c) by compensating loss in the "mind's eye" due to interference and decay. A computer model implementing the main ideas of the theory is presented, and simulations of its search behaviour are discussed. The template theory accounts for the slight skill difference in average depth of search found in chess players, as well as for other empirical data

Expertise and intuition: A tale of three theories

Several authors have hailed intuition as one of the defining features of expertise. In particular, while disagreeing on almost anything that touches on human cognition and artificial intelligence, Hubert Dreyfus and Herbert Simon agreed on this point. However, the highly influential theories of intuition they proposed differed in major ways, especially with respect to the role given to search and as to whether intuition is holistic or analytic. Both theories suffer from empirical weaknesses. In this paper, we show how, with some additions, a recent theory of expert memory (the template theory) offers a coherent and wide-ranging explanation of intuition in expert behaviour. It is shown that the theory accounts for the key features of intuition: it explains the rapid onset of intuition and its perceptual nature, provides mechanisms for learning, incorporates processes showing how perception is linked to action and emotion, and how experts capture the entirety of a situation. In doing so, the new theory addresses the issues problematic for Dreyfus’s and Simon’s theories. Implications for research and practice are discussed

Chunks hierarchies and retrieval structures: Comments on Saariluoma and Laine

The empirical results of Saariluoma and Laine (in press) are discussed and their computer simulations are compared with CHREST, a computational model of perception, memory and learning in chess. Mathematical functions such as power functions and logarithmic functions account for Saariluoma and Laine's (in press) correlation heuristic and for CHREST very well. However, these functions fit human data well only with game positions, not with random positions. As CHREST, which learns using spatial proximity, accounts for the human data as well as Saariluoma and Laine's (in press) correlation heuristic, their conclusion that frequency-based heuristics match the data better than proximity-based heuristics is questioned. The idea of flat chunk organisation and its relation to retrieval structures is discussed. In the conclusion, emphasis is given to the need for detailed empirical data, including information about chunk structure and types of errors, for discriminating between various learning algorithms

Recall of random and distorted positions: Implications for the theory of expertise.

This paper explores the question, important to the theory of expert performance, of the nature and number of chunks that chess experts hold in memory. It examines how memory contents determine players' abilities to reconstruct (a) positions from games, (b) positions distorted in various ways and (c) and random positions. Comparison of a computer simulation with a human experiment supports the usual estimate that chess Masters store some 50,000 chunks in memory. The observed impairment of recall when positions are modified by mirror image reflection, implies that each chunk represents a specific pattern of pieces in a specific location. A good account of the results of the experiments is given by the template theory proposed by Gobet and Simon (in press) as an extension of Chase and Simon's (1973a) initial chunking proposal, and in agreement with other recent proposals for modification of the chunking theory (Richman, Staszewski & Simon, 1995) as applied to various recall tasks

Expertise in chess

This chapter provides an overview of research into chess expertise. After an historical background and a brief description of the game and the rating system, it discusses the information processes enabling players to choose good moves, and in particular the trade-offs between knowledge and search. Other topics include blindfold chess, talent, and the role of deliberate practice and tournament experience

Expert chess memory: Revisiting the chunking hypothesis

After reviewing the relevant theory on chess expertise, this paper re-examines experimentally the finding of Chase and Simon (1973a) that the differences in ability of chess players at different skill levels to copy and to recall positions are attributable to the experts' storage of thousands of chunks (patterned clusters of pieces) in long-term memory. Despite important differences in the experimental apparatus, the data of the present experiments regarding latencies and chess relations between successively placed pieces are highly correlated with those of Chase and Simon. We conclude that the 2-second inter-chunk interval used to define chunk boundaries is robust, and that chunks have psychological reality. We discuss the possible reasons why Masters in our new study used substantially larger chunks than the Master of the 1973 study, and extend the chunking theory to take account of the evidence for large retrieval structures (templates) in long-term memory

Templates in chess memory: A mechanism for recalling several boards

This paper addresses empirically and theoretically a question derived from the chunking theory of memory (Chase & Simon, 1973): To what extent is skilled chess memory limited by the size of short-term memory (about 7 chunks)? This question is addressed first with an experiment where subjects, ranking from class A players to grandmasters, are asked to recall up to 5 positions presented during 5 seconds each. Results show a decline of percentage of recall with additional boards, but also show that expert players recall more pieces than is predicted by the chunking theory in its original form. A second experiment shows that longer latencies between the presentation of boards facilitate recall. In a third experiment, a Chessmaster gradually increases the number of boards he can reproduce with higher than 70% average accuracy to nine, replacing as many as 160 pieces correctly. To account for the results of these experiments, a revision of the Chase-Simon theory is proposed. It is suggested that chess players, like experts in other recall tasks, use long-term memory retrieval structures (Chase & Ericsson, 1982) or templates in addition to chunks in STM, to store information rapidly

Mental Imagery and Chunks: Empirical and Computational Findings

To investigate experts’ imagery in chess, players were required to recall briefly-presented positions in which the pieces were placed on the intersections between squares (intersection positions). Position types ranged from game positions to positions where both the piece distribution and location were randomized. Simulations were run with the CHREST model (Gobet & Simon, 2000). The simulations assumed that pieces had to be centered back one by one to the middle of the squares in the mind’s eye before chunks could be recognized. Consistent with CHREST’s predictions, chess players (N = 36), ranging from weak amateurs to grandmasters, exhibited much poorer recall on intersection positions than on standard positions (pieces placed on centers of squares). On the intersection positions, the skill difference in recall was larger on game positions than on the randomized positions. Participants recalled bishops better than knights, suggesting that Stroop-like interference impairs recall of the latter. The data supported both the time parameter in CHREST for shifting pieces in the mind’s eye (125 ms per piece) and the seriality assumption. In general, the study reinforces the plausibility of CHREST as a model of cognition