In a feat reminiscent of the controversial victory by supercomputer'Deep Blue' over world chess champion Garry Kasparov, a computer program has managed to beat a string of professional poker players at the game. DeepStack, as it was called, defeated 10 out of 11 players who took part in a total of 3,000 games as part of a scientific study into artificial intelligence. The 11th player also lost, but by a margin that the researchers decided was not large enough to be statistically significant. This is not the first time a computer has won at poker. Libratus, a program developed by Carnegie Mellon University academics, won $1.76m (£1.4m) from professionals in January, for example.
Twenty years have passed since the IBM computer Deep Blue defeated world chess champion Garry Kasparov, and we all know computers have improved since then. But Deep Blue won through sheer computing power, using its ability to calculate the outcomes of more moves to a deeper level than even a world champion can. Go is played on a far larger board (19 by 19 squares, compared to 8x8 for chess) and has more possible moves than there are atoms in the universe, so raw computing power was unlikely to beat a human with a strong intuitive sense of the best moves. Instead, AlphaGo was designed to win by playing a huge number of games against other programs and adopting the strategies that proved successful. You could say that AlphaGo evolved to be the best Go player in the world, achieving in only two years what natural selection took millions of years to accomplish.
Fernand Gobet ESR Centre for Research in Development, Instruction and Training Department of Psychology University of Nottingham University Park Nottingham NG7 2RD England firstname.lastname@example.org Abstract Sadly, progress in AI has confirmed earlier conclusions, reached using formal domains, about the strict limits of human information processing and has also shown that these limits are only partly remedied by intuition. More positively, AI offers mankind a unique avenue to circumvent its cognitive limits: (1) by acting as a prosthesis extending processing capacity and size of the knowledge base; (2) offering tools for studying our own cognition; and (3) as consequence of the previous item, by developing tools that increase the quality and quantity of our own thinking. These ideas are illustrated with chess expertise. "...The main thing needed to make the world happy is intelligence. And this, after all, is an optimistic conclusion, because intelligence is a thing that can be fostered by known methods of education."
The big news on March 12 of this year was of the Go-playing AI-system AlphaGo securing victory against 18-time world champion Lee Se-dol by winning the third straight game of a five-game match in Seoul, Korea. After Deep Blue's victory against chess world champion Gary Kasparov in 1997, the game of Go was the next grand challenge for game-playing artificial intelligence. Go has defied the brute-force methods in game-tree search that worked so successfully in chess. In 2012, Communications published a Research Highlight article by Sylvain Gelly et al. on computer Go, which reported that "Programs based on Monte-Carlo tree search now play at human-master levels and are beginning to challenge top professional players." AlphaGo combines tree-search techniques with search-space reduction techniques that use deep learning.
It's been an emotional week in the realm of game AI as the world watched the historic five-game showdown between legendary Go world champion Lee Sedol and Google DeepMind's famed deep learning AI AlphaGo. All five games were held at the Four Seasons Hotel in Seoul, South Korea, and as events played out, millions around the world became increasingly captivated. Anticipation for the match began growing in January, when Google's UK-based AI group DeepMind, led by CEO Demis Hassabis, announced their computer algorithm AlphaGo defeated three-time European Go champion Fan Hui 5 games to 0--a victory some experts didn't expect a computer to achieve for a decade. At the end of a Google blog post announcing the win was the promise of a best-of-five face-off between AlphaGo and 18-time international Go champion Lee Sedol, a match equivalent to IBM's Deep Blue defeat of Garry Kasparov in chess in 1997. Notably, Go is inherently more complex than chess and AlphaGo, at least in part, trained itself to play the game.