Artificial intelligence in the game of go

Early in the film "A Beautiful Mind," the mathematician John Nash is seen sitting in a Princeton courtyard, hunched over a playing board covered with small black and white pieces that look like pebbles. He was playing Go, an ancient Asian game. Frustration at losing that game inspired the real Nash to pursue the mathematics of game theory, research for which he eventually was awarded a Nobel Prize.

In recent years, computer experts, particularly those specializing in artificial intelligence, have felt the same fascination and frustration. Programming other board games has been a relative snap. Even aion kinachess has succumbed to the power of the processor. Five years ago, a chess-playing computer called Deep Blue not only beat but thoroughly humbled Garry Kasparov, the world champion at that time. That is because chess, while highly complex, can be reduced to a matter of brute force computation. Go is different. Deceptively easy to learn, either for a computer or a human, it is a game of such depth and complexity that it can take years for a person to become a strong player. To date, no computer has been able to achieve a skill level beyond that of the casual player.

The game is played on a board divided into a grid of 19 horizontal and 19 vertical lines. Black and white pieces called stones are placed one at a time on the grid's intersections. The object is to acquire and defend territory by surrounding it with aion kinah stones. Programmers working on Go see it as more accurate than chess in reflecting the ways the human mind works. The challenge of programming a computer to mimic that process goes to the core of artificial intelligence, which involves the study of learning and decision-making, strategic thinking, knowledge representation, pattern recognition and perhaps most intriguingly, intuition.
Danny Hillis, a computer designer and chairman of the technology company Applied Minds, said the depth of Go made it ripe for the kind of scientific progress that came from studying one example in great detail.

In the course of a chess game, a player has an average of 25 to 35 moves available. In Go, on the other hand, a player can choose from an average of 240 moves. A Go-playing computer would need about 30,000 years to look as far ahead as Deep Blue can with chess in three seconds, said Michael Reiss, a computer scientist in London. But the obstacles go deeper than processing power. Not only do Go programs have trouble evaluating positions quickly; they have trouble evaluating them corectly. Nonetheless, the allure of computer Go incereases as the difficulties it poses encourages programmers to advance basic work in artificial intelligence.
For that reason, Fotland said, "writing a strong Go program will teach us more about making computers think like people than writing a strong chess program."