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arXiv:2510.23772cs.AI

Evaluating In Silico Creativity: An Expert Review of AI Chess Compositions

Vivek Veeriah, Federico Barbero, Marcus Chiam, Xidong Feng, Michael Dennis, Ryan Pachauri, Thomas Tumiel, Johan Obando-Ceron, Jiaxin Shi, Shaobo Hou, Satinder Singh, Nenad Tomašev, Tom Zahavy

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Abstract

The rapid advancement of Generative AI has raised significant questions regarding its ability to produce creative and novel outputs. Our recent work investigates this question within the domain of chess puzzles and presents an AI system designed to generate puzzles characterized by aesthetic appeal, novelty, counter-intuitive and unique solutions. We briefly discuss our method below and refer the reader to the technical paper for more details. To assess our system's creativity, we presented a curated booklet of AI-generated puzzles to three world-renowned experts: International Master for chess compositions Amatzia Avni, Grandmaster Jonathan Levitt, and Grandmaster Matthew Sadler. All three are noted authors on chess aesthetics and the evolving role of computers in the game. They were asked to select their favorites and explain what made them appealing, considering qualities such as their creativity, level of challenge, or aesthetic design.

arXiv comments
Accepted at the Creative AI Track, NeurIPS 2025
Journal reference
DOI
Subjects
cs.AIArtificial Intelligence cs.LGMachine Learning

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