ARTIFICIAL INTELLIGENCE

(AI), the use of computers to model the behavioral aspects of human reasoning and learning. Research in AI is concentrated in some half-dozen areas. In problem solving, one must proceed from a beginning (the initial state) to the end (the goal state) via a limited number of steps; AI here involves an attempt to model the reasoning process in solving a problem, such as the proof of a theorem in Euclidean geometry. In game theory (see games, theory of), the computer must choose among a number of possible "next" moves to select the one that optimizes its probability of winning; this type of choice is analogous to that of a chess player selecting the next move in response to an opponent's move. In pattern recognition, shapes, forms, or configurations of data must be identified and isolated from a larger group; the process here is similar to that used by a doctor in classifying medical problems on the basis of symptoms. Natural language processing is an analysis of current or colloquial language usage without the sometimes misleading effect of formal grammars; it is an attempt to model the learning process of a translator faced with the phrase "throw mama from the train a kiss." Cybernetics is the analysis of the communication and control processes of biological organisms and their relationship to mechanical and electrical systems; this study could ultimately lead to the development of "thinking" robots (see robotics). Machine learning occurs when a computer improves its performance of a task on the basis of its programmed application of AI principles to its past performance of that task.

In the public eye advances in chess-playing computer programs have become symbolic of progress in AI. In 1948 British mathematician Alan Turing developed a chess algorithm for use with calculating machines—it lost to an amateur player in the one game that it played. Ten years later American mathematician Claude Shannon articulated two chess-playing algorithms: brute force, in which all possible moves and their consequences are calculated as far into the future as possible; and selective mode, in which only the most promising moves and their more immediate consequences are evaluated. In 1988 Hitech, a program developed at Carnegie-Mellon Univ., defeated former U.S. champion Arnold Denker in a four-game match, becoming the first computer to defeat a grandmaster. A year later, Gary Kasparov, the reigning world champion, bested Deep Thought, a program developed by the IBM Corp., in a two-game exhibition. In 1990 the German computer Mephisto-Portrose became the first program to defeat a former world champion; while playing an exhibition of 24 simultaneous games, Anatoly Karpov bested 23 human opponents but lost to the computer. Kasparov in 1996 became the first reigning world champion to lose to a computer in a game played with regulation time controls; the Deep Blue computer, developed by the IBM Corp., won the first game of the match, lost the second, drew the third and fourth, and lost the fifth and sixth. Deep Blue used the brute force approach, evaluating more than 100 billion chess positions each turn while looking six moves ahead; it coupled this with the most efficient chess evaluation software yet developed and an extensive library of chess games it could analyze as part of the decision process. Subsequent matches between Vladimir Kramnik and Deep Fritz (2002) and Kasparov and Deep Junior (2003) have resulted in ties. Unlike Deep Blue, which was a specially designed computer, these more recent computer challengers are chess programs that run on personal computers. Such programs have become an important tool in chess, and are used by chess masters to analyze games and experiment with new moves.

See D. Freedman, Brainmakers: How Scientists Are Moving Beyond Computers to Create a Rival to the Human Brain (1994); D. Gelernter, The Muse in the Machine: Computerizing the Poetry of Human Thought (1994).

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