New AlphaZero Paper Explores Chess Variants
Por um escritor misterioso
Last updated 22 fevereiro 2025
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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
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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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PDF) Brick Tic-Tac-Toe: Exploring the Generalizability of AlphaZero to Novel Test Environments
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Acquisition of Chess Knowledge in AlphaZero – arXiv Vanity
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Chess: Models, code, and papers - CatalyzeX
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Mastering Atari, Go, chess and shogi by planning with a learned model
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DeepMind's AlphaZero AI Helps Design New Chess Rules, by Chintan Trivedi, deepgamingai
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Google AI Achieves Alien Superhuman Mastery of Chess and Go in Mere Hours - The New Stack
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Machine Learning Spotlight gallery – Weights & Biases
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Opening book based on Leela (AlphaZero) policy data : r/chess
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