Abstract

Linhares and Freitas (2010; LF) argue that experts use analogical or semantic similarity, similarities that are not available from direct surface representations. LF make their case using a critique of Chase and Simon (1973b) and the presentation of a few chess positions and examples from other domains. Their conclusion is that models such as CHREST ( Gobet et al., 2001) and theories such as the chunking theory ( Chase & Simon, 1973b) and the template theory ( Gobet & Simon, 1996a, 1996b) are inadequate for dealing with these issues. They propose an alternative paradigm, which they call “experience recognition.” Although we find this issue an interesting one, the separation between pattern recognition and problem solving is a lot more complex than LF portray. We instead suggest that a “revolution” in our to date successful modelling is not necessary. Especially in the chess domain, LF’s examples do not make the point they claim. Furthermore, their criticisms of CS are incorrect, and they have failed to mention a large number of experimental results that have supported the hypothesis of location-specific encodings. Although we agree that experts use semantic information and similarities, these ideas already possess analogues in CHREST, which can form the basis of further evolution of the theory.

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