AlphaGo is a computer program that plays the board game Go. It was made by DeepMind Technologies (Google affiliate). This program became famous due to the victories against professional players.
After the release of AlphaGo, DeepMind Technologies has made powered versions such as the AlphaGo Zero and the AlphaZero: AlphaZero is a self-taught program. This means that it became powerful without human guidance.
The following table is the summary of AlphaGo achievements (including its variants).
|AlphaGo versus Fan Hui||176 GPUs,distributed||3,144||Oct 2015||5:0 against Fan Hui (professional player)|
|AlphaGo versus Lee Sedol||48 Tensor processing units (TPUs), distributed||3,739||Mar 2016||4:1 against Lee Sedol (former Korean & world champion)|
|AlphaGo Master||4 TPUs, single machine||4,858||May 2017||60:0 against professional players|
|AlphaGo Zero (40 block)||4 TPUs, single machine||5,185||Oct 2017||100:0 against AlphaGo version that defeated Lee Sedol
89:11 against AlphaGo Master
|AlphaZero (20 block)||4 TPUs, single machine||5,018||Dec 2017||60:40 against AlphaGo Zero (20 block)|
After the appearance of AlphaGo, several research groups have created computer Go programs with similar technical viewpoints.
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- Marcus, G. (2018). Innateness, alphazero, and artificial intelligence. arXiv preprint arXiv:1801.05667.
- Tian, Y., Ma, J., Gong, Q., Sengupta, S., Chen, Z., Pinkerton, J., & Zitnick, C. L. (2019). Elf opengo: An analysis and open reimplementation of alphazero. arXiv preprint arXiv:1902.04522.
- Bratko, I. (2018). AlphaZero–what’s missing?. Informatica, 42(1).
- Dalgaard, M., Motzoi, F., Sorensen, J. J., & Sherson, J. (2020). Global optimization of quantum dynamics with AlphaZero deep exploration. npj Quantum Information, 6(1)
- Xu, L. (2018, December). Deep bidirectional intelligence: AlphaZero, deep IA-search, deep IA-infer, and TPC causal learning. In Applied Informatics (Vol. 5, No. 1, p. 5). Springer Berlin Heidelberg.
- The New Yorker, How the Artificial-Intelligence Program AlphaZero Mastered Its Games, By James Somers, December 28, 2018.
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- Tian, Yuandong; Zhu, Yan (2015). "Better Computer Go Player with Neural Network and Long-term Prediction". arXiv:1511.06410v1 [cs.LG].
- "facebookresearch/darkforestGo". Facebook Research. 16 March 2021.
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- Wu, T. R., Wu, I. C., Chen, G. W., Wei, T. H., Wu, H. C., Lai, T. Y., & Lan, L. C. (2018). Multi-labeled value networks for computer Go. IEEE Transactions on Games, 10(4), 378-389.
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