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"

Simplifying MuZero in Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model — Andrew Silva

Frontiers AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong

Is AlphaZero really a scientific breakthrough in AI?, by Jose Camacho Collados

PDF) Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Othello is Solved – arXiv Vanity

Chess & Shogi with General Reinforcement Learning Algorithm – Coding Ninjas Blog

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

PDF) A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
GitHub - zjeffer/chess-deep-rl: Research project: create a chess engine using Deep Reinforcement Learning
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