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Researchers in the field of artificial intelligence have long been intrigued by games, and not just as a way of avoiding work. G
Researchers in the field of artificial intelligence have long been intrigued by games, and not just as a way of avoiding work. G
admin
2017-04-13
49
问题
Researchers in the field of artificial intelligence have long been intrigued by games, and not just as a way of avoiding work. Games provide an ideal setting to explore important elements of the design of cleverer machines, such as pattern recognition, learning and planning. They also hold out the tantalizing possibility of fame and fortune should the program ever beat a human champion.
Ever since the stunning victory of Deep Blue, a program running on an IBM supercomputer, over Gary Kasparov, then world chess champion, in 1997, it has been clear that computers would dominate that particular game. Today, though, they are pressing the attack on every front. There is one game, however, where humans still reign supreme Go. Yet here too their grip is beginning to loosen.
Go was invented more than 2,500 years ago in China. It is a strategic contest in which two players take turns to place stones on the intersections of a grid with 19 lines on each side. Each player tries to stake out territory and surround his opponent. The rules are simple but the play is extraordinarily complex. During a game, some stones will "die", and some will appear to be dead but spring back to life at an ill-timed moment. It is often difficult to say who is winning right until the end.
Deep Blue beat Mr. Kasparov using the "brute force" technique. Rather than search for the best move in a given position, the computer considers all white’s moves, and all black’s possible replies, and all white’s replies to those replies, and so on for, say, a dozen turns. The resulting map of possible moves has millions of branches. The computer combs through the possible outcomes and plays the one move that would give its opponent the fewest chances of winning. Unfortunately, brute force will not work in Go. First, the game has many more possible positions than chess does. Second, the number of possible moves from a typical position in Go is about 200, compared with about a dozen in chess. Finally, evaluating a Go position is
fiendishly
difficult. The fastest programs can assess just 50 positions a second, compared with 500,000 in chess.
In the past two decades researchers have explored several alternative strategies with indifferent results. Now, however, programmers are making impressive gains with a technique known as the Monte Carlo method. Given a position, a program using a Monte Carlo algorithm contemplates every move and plays a large number of random games to see what happens. If it wins in 80% of those games, the move is probably good. Otherwise, it keeps looking. The result is a new generation of fast programs that play particularly well on small versions of the Go board.
According to Paragraph 1, computer games could
选项
A、promote the researches of human intelligence.
B、help researchers avoid work.
C、serve to improve the program designing.
D、bring fame and fortune to the human champion.
答案
C
解析
事实细节题。文章首段第二句指出“游戏为探究更智能机器设计提供了一个非常理想的框架”,C项符合文意。
转载请注明原文地址:https://kaotiyun.com/show/z1bZ777K
0
考研英语一
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