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Emergent complexity in the decision-making process of chess players
Andrés Chacoma1,2, Orlando V Billoni3,4
1Instituto de Física Interdisciplinaria y Aplicada, CONICET-Universidad de Buenos Aires, Buenos Aires, Argentina. achacoma@df.uba.ar.
Scientific Reports
|July 2, 2025
Summary
Chess players
Area of Science:
- Cognitive science
- Computational psychology
- Game theory
Background:
- Understanding chess player decision-making is complex.
- Quantifying move decisiveness is crucial for analysis.
Purpose of the Study:
- To analyze chess player decision-making using a novel metric.
- To compare decision-making across different skill levels.
Main Methods:
- Utilized a chess engine for move evaluation.
- Developed a decisiveness metric based on engine evaluations.
- Conducted comparative analysis across player skill levels.
Main Results:
- Observed a wide spectrum of move decisiveness, indicating process complexity.
- Found that decreased complexity correlates with lower player performance.
- Player accuracy increases in high-decisiveness positions, irrespective of skill level.
- Characterized decision-making by minimizing the decisiveness metric.
Conclusions:
- A simple model replicating emergent properties was proposed.
- Decision-making complexity may be linked to chess performance.
- Accuracy is enhanced in complex, high-decisiveness positions.
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