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Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2131

Title: Memory for the meaningless: How chunks help
Authors: Gobet, F
Keywords: chess
CHREST
chunking
computer modeling
game positions
random positions
presentation time
EPAM
memory
task
skill
expertise
short-term memory capacity
STM capacity
Publication Date: 1998
Publisher: Erlbaum
Citation: Gobet, F. (1998). Memory for the meaningless: How chunks help. Proceedings of the 20th Meeting of the Cognitive Science Society. (pp. 398-403). Mahwah, NJ: Erlbaum.
Abstract: 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.
URI: http://bura.brunel.ac.uk/handle/2438/2131
Appears in Collections:School of Social Sciences Research Papers
Psychology

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