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Related Experiment Video

Updated: Jul 21, 2025

A Protocol for Computer-Based Protein Structure and Function Prediction

A Protocol for Computer-Based Protein Structure and Function Prediction

Published on: November 3, 2011

Searching for answers: expert pattern recognition and planning.

Fernand Gobet¹, Andrew J Waters²

¹London School of Economics and Political Science, London, UK.

Trends in Cognitive Sciences

|July 28, 2023

Summary

This summary is machine-generated.

Expertise in games develops through increased search depth, not just pattern recognition. As players improve their skill, they engage in more extensive cognitive search strategies.

Keywords:

board games chunking expertise modeling pattern recognition search

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Area of Science:

Cognitive Psychology
Artificial Intelligence
Human-Computer Interaction

Background:

Debate on the origins of expertise: pattern recognition vs. search depth.
Understanding skill acquisition in complex tasks is crucial for AI and psychology.

Purpose of the Study:

Investigate whether expertise primarily arises from pattern recognition or search depth.
Develop and test a new model explaining skill acquisition in a board game context.

Main Methods:

Multi-method, multi-experiment study using a novel board game.
Analysis of player behavior correlating skill improvement with search depth.

Main Results:

Players demonstrably increase their search depth as their skill level improves.
Findings challenge the sole reliance on pattern recognition as the driver of expertise.

Conclusions:

Skill acquisition in this board game is significantly linked to an increased depth of cognitive search.
Suggests that search depth is a critical component of expertise development in strategic tasks.