Google's 'superhuman' DeepMind AI claims chess crown

From BBC - December 6, 2017

Google says its AlphaGo Zero artificial intelligence program has triumphed at chess against world-leading specialist software within hours of teaching itself the game from scratch.

The firm's DeepMind division says that it played 100 games against Stockfish 8, and won or drew all of them.

The research has yet to be peer reviewed.

But experts already suggest the achievement will strengthen the firm's position in a competitive sector.

"From a scientific point of view, it's the latest in a series of dazzling results that DeepMind has produced," the University of Oxford's Prof Michael Wooldridge told the BBC.

"The general trajectory in DeepMind seems to be to solve a problem and then demonstrate it can really ramp up performance, and that's very impressive."

DeepMind has previously defeated several of the world's top human players of the Chinese board game Go, as well as teaching itself how to play video games including Pong and Space Invaders.

The London-based team is currently trying to develop a system that can beat humans at the space strategy game Starcraft, which is seen as being an even more complex challenge.

Thinking time

Google is not commenting on the research until it is published in a journal.

However, details published on Cornell University's Arxiv site state that an algorithm dubbed AlphaZero was able to outperform Stockfish just four hours after being given the rules of chess and being told to learn by playing simulations against itself.

In the 100 matches that followed, each program was given one minute's worth of thinking time per move.

AlphaZero won 25 games in which it played with white pieces, giving it the first move, and a further three in which it played with black pieces.

The two programs drew the remaining 72 games.

DeepMind described the level of performance achieved as being "superhuman"

Google highlighted that Stockfish 8 had previously won 2016's Top Chess Engine Championship. The software was first released in 2008 and has been built on by volunteers in the years since.

Open v closed


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