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Human grandmasters were generally impressed with AlphaZero's games against Stockfish. [23] Former world champion Garry Kasparov said it was a pleasure to watch AlphaZero play, especially since its style was open and dynamic like his own. [24] [25]
This essentially meant AlphaZero could learn chess by itself. The initial tests with AlphaZero were staggering; in a 100 game match against the current strongest engine Stockfish, AlphaZero won 28 games and tied the remaining 72. [12] In many ways AlphaZero served not only as a breakthrough for chess computing, but for the AI world in general.
Leela vs Stockfish, CCCC bonus games, 1–0 Leela beats the world champion Stockfish engine despite a one-pawn handicap. Stockfish vs Leela Chess Zero – TCEC S15 Superfinal – Game 61 Leela completely outplays Stockfish with black pieces in the Trompovsky attack. Leela's eval went from 0.1 to −1.2 in one move, and Stockfish's eval did not ...
By January 2019, Leela was able to defeat the version of Stockfish that played AlphaZero (Stockfish 8) in a 100-game match. An updated version of Stockfish narrowly defeated Leela Chess Zero in the superfinal of the 14th TCEC season, 50.5–49.5 (+10 =81 −9), [37] but lost the Superfinal of the next season to Leela 53.5–46.5 (+14 =79 -7).
MuZero (MZ) is a combination of the high-performance planning of the AlphaZero (AZ) algorithm with approaches to model-free reinforcement learning. The combination allows for more efficient training in classical planning regimes, such as Go, while also handling domains with much more complex inputs at each stage, such as visual video games.
Stockfish finally scored a win in game 35, but failed to hold the reverse game, and after Leela won game 38 the gap widened further to five games. There was a glimmer of hope for Stockfish when it won games 43 and 45 to narrow the gap to 3 points, but Leela scored a decisive victory in games 61 and 62, outplaying Stockfish with both the white ...
Kaufman has tried to compare White's first-move advantage with various positional or material advantages by having engines play games from modified versions of the opening position: he concludes that "if we define 1.00 as the advantage of a clean extra pawn in the opening with all other factors being equal, it takes above a 0.70 advantage in ...
Google later developed AlphaZero, a generalized version of AlphaGo Zero that could play chess and Shōgi in addition to Go. [7] In December 2017, AlphaZero beat the 3-day version of AlphaGo Zero by winning 60 games to 40, and with 8 hours of training it outperformed AlphaGo Lee on an Elo scale.