Deep Mind has just announced AlphaGo Zero, an evolution of AlphaGo, the first computer program to defeat a world champion at the ancient Chinese game of Go. Zero is even more powerful and is now arguably the strongest Go player in history, according to the company.

While previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go, AlphaGo Zero skips this step. It learns to play from scratch, simply by playing games against itself, starting from completely random play.

It surpassed Alpha Lee in 3 days, then surpassed human level of play, defeating the previously published champion-defeating version of AlphaGo by 100 games to 0 in just 40 days.

The achievement is described in the journal Nature today (Oct. 18, 2017)

DeepMind | AlphaGo Zero: Starting from scratch

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Abstract of Mastering the game of Go without human knowledge

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves using deep neural networks. These neural networks were trained by supervised learning from human expert moves, and by reinforcement learning from self-play. Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules. AlphaGo becomes its own teacher: a neural network is trained to predict AlphaGo’s own move selections and also the winner of AlphaGo’s games. This neural network improves the strength of the tree search, resulting in higher quality move selection and stronger self-play in the next iteration. Starting tabula rasa, our new program AlphaGo Zero achieved superhuman performance, winning 100–0 against the previously published, champion-defeating AlphaGo.