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Since DeepMind's AlphaZero, Zero learning quickly became the state-of-the-art method for many board games.
Realization of a general game-playing program
J. Pitrat · 1968
Earlier work this paper cites.
Bandit based Monte-Carlo planning
L. Kocsis and C. Szepesvári · 2006
Earlier work this paper cites.
General game playing: Game description language specification
N. Love, T. Hinrichs, and M. Genesereth · 2006
Earlier work this paper cites.
Set colouring games
J. van Rijswijck · 2006
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Efficient selectivity and backup operators in Monte-Carlo tree search
R. Coulom · 2007
Earlier work this paper cites.
Optimistic Heuristics for MineSweeper
O. Buffet, C.-S. Lee, W. Lin, and O. Teytaud · 2012
Cited alongside, same era.
Early playout termination in mcts
R. Lorentz · 2015
Cited alongside, same era.
On the complexity of connection games
É. Bonnet, F. Jamain, and A. Saffidine · 2016
Cited alongside, same era.
Mastering the game of Go with deep neural networks and tree search
D. Silver, A. Huang, C. J. Maddison, A. Guez, L. Sifre, G. van den Driessche, J. Schrittwieser, I. Antonoglou, V. Panneershelvam, M. Lanctot, S. Dieleman, D. Grewe, J. Nham, N. Kalchbrenner, I. Sutskever, T. Lillicrap, M. Leach, K. Kavukcuoglu, T. Graepel, and D. Hassabis · 2016
Cited alongside, same era.
Leela zero
G.-C. Pascutto · 2017
Cited alongside, same era.
Mastering chess and shogi by self-play with a general reinforcement learning algorithm
D. Silver, T. Hubert, J. Schrittwieser, I. Antonoglou, M. Lai, A. Guez, M. Lanctot, L. Sifre, D. Kumaran, T. Graepel, T. P. Lillicrap, K. Simonyan, and D. Hassabis · 2017
Later among the works it cites.
Galvanise zero
R. Emslie · 2019
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Elf opengo: An analysis and open reimplementation of alphazero
Y. Tian, Jerry Ma*, Qucheng Gong*, Shubho Sengupta*, Z. Chen, J. Pinkerton, and C. L. Zitnick · 2019
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Accelerating self-play learning in go
D. J. Wu · 2019
Later among the works it cites.
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