Mastering the game of Go with deep neural networks and tree search
The game of Go has long been viewed as the most challenging of classic games for artificial intelligence. The journal Nature reported on 28 January that researchers at Google Deepmind developed AlphaGo, a program based on neural networks, policy gradient and Monte Carlo tree search that achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.
Thore Graepel, one of the authors on the paper, will present the results during the Intelligent Machines day on 22 March 2016 in de Flint in Amersfoort.