Figure 1 from Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
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Last updated 09 fevereiro 2025
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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"
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PDF] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
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Resource Management for Internet of Things Environments
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Training AlphaZero for 700,000 steps. Elo ratings were computed from
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Mastering construction heuristics with self-play deep reinforcement learning
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Electronics, Free Full-Text
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Reinforcement Learning, Fast and Slow: Trends in Cognitive Sciences
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Alessandro Vespignani on X: A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play “a program called AlphaZero, which taught itself to play Go, chess, and shogi” /
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Reinforcement learning is all you need, for next generation language models.
A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
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Mastering Atari, Go, chess and shogi by planning with a learned model
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PDF) A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
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Mastering chess and shogi by self-play with a general reinforcement learning algorithm
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PDF) Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm
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A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play
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