Figure 1 from Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
Por um escritor misterioso
Last updated 26 dezembro 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"
AlphaGomoku: An AlphaGo-based Gomoku Artificial Intelligence using Curriculum Learning – arXiv Vanity
AlphaZero paper discussion (Mastering Go, Chess, and Shogi) • Life In 19x19
Full article: Time management in a chess game through machine learning
Mastering Atari, Go, chess and shogi by planning with a learned model
Two-stage training algorithm for AI robot soccer [PeerJ]
Reinforcement learning applied to games
Electronics, Free Full-Text
Create AI for your Own Board Game From Scratch — AlphaZero-Part 3, by Haryo Akbarianto Wibowo
Computational Models of Cognition: Part VII: Reinforcement Learning, by Alireza Dehbozorgi
David Silver (et al.), A general
AlphaZero: The AI from Google which mastered Chess in 4 hours, by University of Toronto Machine Intelligence Team
AlphaZero, Lecture 82 (Part 2)
PDF] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
Electronics, Free Full-Text
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