New AlphaZero Paper Explores Chess Variants
Por um escritor misterioso
Last updated 17 março 2025

In a new paper from DeepMind, this time co-written by 14th world chess champion Vladimir Kramnik, the self-learning chess engine AlphaZero is used to explore the design of different variants of the game of chess, with different sets of rules. The paper is titled Assessing Game Balance with AlphaZero

AlphaZero: A General Reinforcement Learning Algorithm that Masters Chess, Shogi and Go through Self-Play

Instead of practicing, this AI mastered chess by reading about it

Acquisition of Chess Knowledge in AlphaZero – arXiv Vanity

Computer Chess: Most Up-to-Date Encyclopedia, News & Reviews

PDF] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

IJERPH, Free Full-Text

Checkmate: how we mastered the AlphaZero cover, Science

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Reimagining Chess with AlphaZero, February 2022

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AlphaZero: A General Reinforcement Learning Algorithm that Masters Chess, Shogi and Go through Self-Play
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