Computer Go

Computer Go is the field of artificial intelligence (AI) dedicated to creating a computer program that plays the traditional board game Go. The game of Go has been a fertile subject of artificial intelligence research for decades, culminating in 2017 with AlphaGo Master winning three of three games against Ke Jie, who at the time continuously held the world No. 1 ranking for two years.Go on a computer? – In order to programme a computer to play a reasonable game of Go, rather than merely a legal game – it is necessary to formalise the principles of good strategy, or to design a learning programme. The principles are more qualitative and mysterious than in chess, and depend more on judgment. So I think it will be even more difficult to programme a computer to play a reasonable game of Go than of chess. Computer Go is the field of artificial intelligence (AI) dedicated to creating a computer program that plays the traditional board game Go. The game of Go has been a fertile subject of artificial intelligence research for decades, culminating in 2017 with AlphaGo Master winning three of three games against Ke Jie, who at the time continuously held the world No. 1 ranking for two years. Go is a complex board game that requires intuition, creative and strategic thinking. It has long been considered a difficult challenge in the field of artificial intelligence (AI) and is considerably more difficult to solve than chess. Many in the field of artificial intelligence consider Go to require more elements that mimic human thought than chess. Mathematician I. J. Good wrote in 1965: Prior to 2015, the best Go programs only managed to reach amateur dan level. On the small 9×9 board, the computer fared better, and some programs managed to win a fraction of their 9×9 games against professional players. Prior to AlphaGo, some researchers had claimed that computers would never defeat top humans at Go. The first Go program was written by Albert Lindsey Zobrist in 1968 as part of his thesis on pattern recognition. It introduced an influence function to estimate territory and Zobrist hashing to detect ko. In April 1981, Jonathan K Millen published an article in Byte discussing Wally, a Go program with a 15x15 board that fit within the KIM-1 microcomputer's 1K RAM. Bruce F. Webster published an article in the magazine in November 1984 discussing a Go program he had written for the Apple Macintosh, including the MacFORTH source. In 1998, very strong players were able to beat computer programs while giving handicaps of 25–30 stones, an enormous handicap that few human players would ever take. There was a case in the 1994 World Computer Go Championship where the winning program, Go Intellect, lost all three games against the youth players while receiving a 15-stone handicap. In general, players who understood and exploited a program's weaknesses could win with much larger handicaps than typical players. Developments in Monte Carlo tree search and machine learning brought the best programs to high dan level on the small 9x9 board. In 2009, the first such programs appeared which could reach and hold low dan-level ranks on the KGS Go Server on the 19x19 board as well. In 2010, at the 2010 European Go Congress in Finland, MogoTW played 19x19 Go against Catalin Taranu (5p). MogoTW received a seven-stone handicap and won. In 2011, Zen reached 5 dan on the server KGS, playing games of 15 seconds per move. The account which reached that rank uses a cluster version of Zen running on a 26-core machine.