Figure 1 from Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
Por um escritor misterioso
Last updated 12 abril 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"

AlphaZero paper discussion (Mastering Go, Chess, and Shogi) • Life In 19x19

Mastering Atari, Go, chess and shogi by planning with a learned model

Reinforcement Learning: A Quick Overview, by Mohit Pilkhan

Reinforcement Learning, Fast and Slow: Trends in Cognitive Sciences

AlphaZero: The AI from Google which mastered Chess in 4 hours, by University of Toronto Machine Intelligence Team

Algorithms, Free Full-Text

Electronics, Free Full-Text

Reinforcement learning applied to games

Electronics, Free Full-Text

Shogi - Wikipedia

Mastering construction heuristics with self-play deep reinforcement learning

PDF] Exploring the Performance of Deep Residual Networks in Crazyhouse Chess

Computational Models of Cognition: Part VII: Reinforcement Learning, by Alireza Dehbozorgi
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