Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 191

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

The Roles of Recognition Processes and Look-Ahead Search in Time-Constrained Expert Problem Solving: Evidence From Grand-Master-Level Chess

Open access
Gobet, Fernand, Simon, Herbert A.·1996·Psychological Science

Abstract

Chess has long served as an important standard task environment for research on human memory and problem-solving abilities and processes In this article, we report evidence on the relative importance of recognition processes and planning (look-ahead) processes in very high level expert performance in chess The data show that the rated skill of a top-level grand master is only slightly lower when he is playing simultaneously against a half-dozen grand-master opponents than under tournament conditions that allow much more time for each move As simultaneous play allows little time for look-ahead processes, the data indicate that recognition, based on superior chess knowledge, plays a much larger part in high-level skill in this task than does planning by looking ahead

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/j.1467-9280.1996.tb00666.x

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

See all 191

Metadata

Authors
Gobet, F., & Simon, H. A.
Venue
Psychological Science
Published
1996-01
Volume
7
Issue
1
Pages
52-55
ISSN
  • 0956-7976 (ISSN-L)
  • 1467-9280
OpenAlex
W2112968305
Cited by
191
References
2
FWCI
10.41
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: The Roles of Recognition Processes and Look-Ahead Search in Time-Constrained Expert Problem Solving: Evidence From Grand-Master-Level Chess. https://app.cochat.ai/papers/10.1111/j.1467-9280.1996.tb00666.x
The paper
Gobet, F., & Simon, H. A. (1996). The Roles of Recognition Processes and Look-Ahead Search in Time-Constrained Expert Problem Solving: Evidence From Grand-Master-Level Chess. Psychological Science. https://doi.org/10.1111/j.1467-9280.1996.tb00666.x

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.