(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 were symbolic of early 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, Garry 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, 2006) and Kasparov and Deep Junior (2003) resulted in two ties and a win for the programs. Unlike Deep Blue, which was a specially designed computer, these more recent computer challengers were chess programs running on powerful 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. In 2016 Google's DeepMind AlphaGo defeated one of the world's best go players, Lee Sedol, in a five-game tournament in South Korea; go is considered to be more difficult than chess for a computer program. In 2017 an updated version of the program defeated the world's best go player, Ke Jie, in a three-game tournament.
Another notable IBM AI computer, Watson, competed in 2011 on the “Jeopardy!” television quiz show, defeating two human champions. Watson, about 100 times faster than Deep Blue, was designed to process questions in natural human language (as opposed to simple commands), making sense of the quirky questions' complexity and ambiguity, and to search an extensive database to quickly provide the correct answers. Watson is a prototype for programs or services that can act as knowledgeable assistants, or even human substitutes, in such different fields as medicine, catalog sales, and computer technical support.
The introduction of the smartphone has brought aspects of artificial intelligence to cellular telephones, most prominently in the voice-controlled “personal assistants” that can provide a range of information and recommendations or perform tasks in response to the user's voice commands, to the schedule maintained by the user's calendar application, and the like. First introduced on the Apple smartphone in 2011, such personal assistants have become widely available on smartphones, computer tablets, personal computers, and other electronic devices. Global-positioning system (GPS) devices, or similar smartphone applications, which provide turn-by-turn directions as a person drives, can redirect the driver in real time to avoid traffic jams, and increasingly accept voice commands, are another, more limited but common utilization of advances in artificial intelligence, as are translation and voice-recognition programs. Self-driving automobiles, whether fully autonomous or acting as an assistant to a human driver, are another example of the use of artificial intelligence. Such vehicles use sensor, mapping, and GPS information to locate where they are, rely on sensors and interpretative software to determine what vehicles, people, objects, and the like are nearby, and use computer-controlled systems to drive and maneuver.
See also expert system.
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