Figure 1 from Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
Por um escritor misterioso
Last updated 28 janeiro 2025
Figure 1: Training AlphaZero for 700,000 steps. Elo ratings were computed from evaluation games between different players when given one second per move. a Performance of AlphaZero in chess, compared to 2016 TCEC world-champion program Stockfish. b Performance of AlphaZero in shogi, compared to 2017 CSA world-champion program Elmo. c Performance of AlphaZero in Go, compared to AlphaGo Lee and AlphaGo Zero (20 block / 3 day) (29). - "Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm"
Create AI for your Own Board Game From Scratch — AlphaZero-Part 3, by Haryo Akbarianto Wibowo
Electronics, Free Full-Text
Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
Mastering the game of Go with deep neural networks and tree search
Othello is Solved – arXiv Vanity
AlphaZero: The AI from Google which mastered Chess in 4 hours, by University of Toronto Machine Intelligence Team
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
PDF] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
Alessandro Vespignani on X: A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play “a program called AlphaZero, which taught itself to play Go, chess, and shogi” /
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