Figure 1 from Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
Por um escritor misterioso
Last updated 07 novembro 2024
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"
Applied Sciences, Free Full-Text
Reinforcement learning applied to games
AlphaZero: A General Reinforcement Learning Algorithm that Masters Chess, Shogi and Go through Self-Play
Figure 1 from Giraffe: Using Deep Reinforcement Learning to Play Chess
AlphaZero Research Paper Summary, PDF, Machine Learning
Reinforcement Learning: A Quick Overview, by Mohit Pilkhan
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: A Quick Summary, by Ali Abidi
AlphaZero paper discussion (Mastering Go, Chess, and Shogi) • Life In 19x19
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