Figure 1 from Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
Por um escritor misterioso
Last updated 03 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"
Frontiers AlphaZe∗∗: AlphaZero-like baselines for imperfect information games are surprisingly strong
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AlphaZero: The AI from Google which mastered Chess in 4 hours, by University of Toronto Machine Intelligence Team
Beyond Chess and Go: Why AI Mastering Games Could Be Good News For Everyone - Heidelberg Laureate Forum - SciLogs - Wissenschaftsblogs
Mastering chess and shogi by self-play with a general reinforcement learning algorithm
David Silver (et al.), A general
Giraffe: Using Deep Reinforcement Learning to Play Chess – arXiv Vanity
Reinforcement Learning: A Quick Overview, by Mohit Pilkhan
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