Universality in Collective Intelligence on the Rubik's Cube

Fuente: arXiv
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Hauptverfasser: Krakauer, David, Kardeş, Gülce, Grochow, Joshua
Format: Preprint
Veröffentlicht: 2025
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author Krakauer, David
Kardeş, Gülce
Grochow, Joshua
author_facet Krakauer, David
Kardeş, Gülce
Grochow, Joshua
contents Progress in understanding expert performance is limited by the scarcity of quantitative data on long-term knowledge acquisition and deployment. Here we use the Rubik's Cube as a cognitive model system existing at the intersection of puzzle solving, skill learning, expert knowledge, cultural transmission, and group theory. By studying competitive cube communities, we find evidence for universality in the collective learning of the Rubik's Cube in both sighted and blindfolded conditions: expert performance follows exponential progress curves whose parameters reflect the delayed acquisition of algorithms that shorten solution paths. Blindfold solves form a distinct problem class from sighted solves and are constrained not only by expert knowledge but also by the skill improvements required to overcome short-term memory bottlenecks, a constraint shared with blindfold chess. Cognitive artifacts such as the Rubik's Cube help solvers navigate an otherwise enormous mathematical state space. In doing so, they sustain collective intelligence by integrating communal knowledge stores with individual expertise and skill, illustrating how expertise can, in practice, continue to deepen over the course of a single lifetime.
format Preprint
id arxiv_https___arxiv_org_abs_2511_18609
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Universality in Collective Intelligence on the Rubik's Cube
Krakauer, David
Kardeş, Gülce
Grochow, Joshua
Artificial Intelligence
Computers and Society
Human-Computer Interaction
Progress in understanding expert performance is limited by the scarcity of quantitative data on long-term knowledge acquisition and deployment. Here we use the Rubik's Cube as a cognitive model system existing at the intersection of puzzle solving, skill learning, expert knowledge, cultural transmission, and group theory. By studying competitive cube communities, we find evidence for universality in the collective learning of the Rubik's Cube in both sighted and blindfolded conditions: expert performance follows exponential progress curves whose parameters reflect the delayed acquisition of algorithms that shorten solution paths. Blindfold solves form a distinct problem class from sighted solves and are constrained not only by expert knowledge but also by the skill improvements required to overcome short-term memory bottlenecks, a constraint shared with blindfold chess. Cognitive artifacts such as the Rubik's Cube help solvers navigate an otherwise enormous mathematical state space. In doing so, they sustain collective intelligence by integrating communal knowledge stores with individual expertise and skill, illustrating how expertise can, in practice, continue to deepen over the course of a single lifetime.
title Universality in Collective Intelligence on the Rubik's Cube
topic Artificial Intelligence
Computers and Society
Human-Computer Interaction
url https://arxiv.org/abs/2511.18609