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Related Experiment Videos

Cognitive model of problem-solving in chess.

M J Scurrah, D A Wagner

    Science (New York, N.Y.)
    |July 10, 1970
    PubMed
    Summary
    This summary is machine-generated.

    Behavioral predictability in chess problem-solving was identified through experiments. A developed model explains these patterns, potentially aiding future chess computer programs.

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    Area of Science:

    • Cognitive Science
    • Artificial Intelligence
    • Human-Computer Interaction

    Background:

    • Understanding human problem-solving strategies is crucial for AI development.
    • Chess provides a complex domain for studying cognitive processes.

    Purpose of the Study:

    • To identify predictable patterns in human chess problem-solving behavior.
    • To develop a model explaining observed behavioral predictability.
    • To assess the applicability of identified heuristics in artificial intelligence.

    Main Methods:

    • Conducted five experiments involving two human subjects.
    • Observed and analyzed subject behavior during chess problem-solving tasks.
    • Developed a predictive model based on experimental data.

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    Main Results:

    • Identified several predictable aspects of one subject's chess problem-solving behavior.
    • Successfully developed a model to explain this behavioral predictability.
    • The model's heuristics offer insights into cognitive strategies.

    Conclusions:

    • Human chess problem-solving exhibits predictable patterns.
    • The developed model provides a framework for understanding these patterns.
    • Identified heuristics may inform the design of advanced chess-playing computer programs.