“artificial intelligence”的概念、定义、翻译、参考文献-科学参考

artificial intelligence

Physics

A field of computing concerned with the production of programs that perform tasks requiring intelligence when done by people. These tasks include playing games, such as chess or draughts, forming plans, understanding speech and natural languages, interpreting images, reasoning, and learning.

Statistics

Research in which the aim is to construct an intelligent computing machine, including both hardware and software, that can tackle problems that usually require human intelligence. Such problems include expert systems, the playing of games, and language translation. A major success is the chess-playing machine Deep Blue, although this machine does not emulate human analysis of chess, but uses vast computing power at each stage to consider millions of possible subsequent positions. In 1950, Turing proposed a test for intelligence in a computing machine: an observer, posing questions via a keyboard and obtaining answers on a monitor, must be convinced that a human, rather than a machine, is responding to the questions.

Computer

A discipline concerned with the building of computer programs that perform tasks requiring intelligence when done by humans. However, intelligent tasks for which a decision procedure is known (e.g. inverting matrices) are generally excluded, whereas perceptual tasks that might seem not to involve intelligence (e.g. seeing) are generally included. For this reason, AI is better defined by indicating its range. Examples of tasks tackled within AI are: game playing, automated reasoning, machine learning, natural-language understanding, planning, speech understanding, and theorem proving.
Perceptual tasks (e.g. seeing and hearing) have been found to involve much more computation than is apparent from introspection. This computation is unconscious in humans, which has made it hard to simulate. AI has had relatively more success at intellectual tasks (e.g. game playing and theorem proving) than perceptual tasks. Sometimes these computer programs are intended to simulate human behaviour to assist psychologists and neuroscientists (see cognitive modelling). Sometimes they are built to solve problems for technological application (see expert systems, robotics).
Both theoretical and applied AI research have made very significant contributions to computer science. Computational techniques that originated from AI include augmented transition networks, means/ends analysis, production rule systems, resolution, semantic networks, and heuristic search.
Philosophers have long been interested in the question, ‘can a computer think?’ There are two schools of thought: weak AI, which is the proposition that computers can at least simulate thought and intelligence; and strong AI, which argues that a machine that can perform cognitive tasks is actually thinking. This is a complex topic that has received new interest with a focus on consciousness.

Internet

A discipline that attempts to replicate human skills over some domain; for example, by providing intelligent search facilities.

Electronics and Electrical Engineering

The study and development of computing applications for tasks that would be described as requiring intelligence if they were done by people. Many of these applications involve systems that are capable of learning, adaptation, or self-correction.

Philosophy

The science of making machines that can do the kinds of thing that humans can do. Topics of research have included speech recognition, visual recognition, and the more familiar problem solving and game-playing. Modelling a psychological phenomenon on a computer is a way of showing how the phenomenon is possible in a physical world, and is also a way of bringing out the complexities involved in apparently simple tasks. A central concept in much AI research is that of a representation, with programs designed to construct, adapt, and link representations in the production of intelligent responses. This research has been responsible for a considerable retreat from dogmatic behaviourism, in which the idea of mental manipulations was thought to be unscientific, since it is exactly the storage and manipulation of representations of the world that is demanded in the problems AI approaches. Strong AI is the philosophical thesis that appropriately programmed computers have minds in exactly the same sense that we do. Weak AI is the methodological belief that the best way to explore the mind is to proceed as if this were true, without commenting on the legacies of dualism that lead to discomfort with the strong thesis. See also Chinese room, connectionism, frame problem, Turing test.
http://www.bbc.co.uk/radio4/history/inourtime/inourtime_20051208.shtml An audio discussion of AI by two scientists and a philosopher
http://www.aaai.org/aitopics/html/welcome.html A dynamic library of internet resources on AI

单词	artificial intelligence
释义	artificial intelligence Physics A field of computing concerned with the production of programs that perform tasks requiring intelligence when done by people. These tasks include playing games, such as chess or draughts, forming plans, understanding speech and natural languages, interpreting images, reasoning, and learning. Statistics Research in which the aim is to construct an intelligent computing machine, including both hardware and software, that can tackle problems that usually require human intelligence. Such problems include expert systems, the playing of games, and language translation. A major success is the chess-playing machine Deep Blue, although this machine does not emulate human analysis of chess, but uses vast computing power at each stage to consider millions of possible subsequent positions. In 1950, Turing proposed a test for intelligence in a computing machine: an observer, posing questions via a keyboard and obtaining answers on a monitor, must be convinced that a human, rather than a machine, is responding to the questions. Computer A discipline concerned with the building of computer programs that perform tasks requiring intelligence when done by humans. However, intelligent tasks for which a decision procedure is known (e.g. inverting matrices) are generally excluded, whereas perceptual tasks that might seem not to involve intelligence (e.g. seeing) are generally included. For this reason, AI is better defined by indicating its range. Examples of tasks tackled within AI are: game playing, automated reasoning, machine learning, natural-language understanding, planning, speech understanding, and theorem proving. Perceptual tasks (e.g. seeing and hearing) have been found to involve much more computation than is apparent from introspection. This computation is unconscious in humans, which has made it hard to simulate. AI has had relatively more success at intellectual tasks (e.g. game playing and theorem proving) than perceptual tasks. Sometimes these computer programs are intended to simulate human behaviour to assist psychologists and neuroscientists (see cognitive modelling). Sometimes they are built to solve problems for technological application (see expert systems, robotics). Both theoretical and applied AI research have made very significant contributions to computer science. Computational techniques that originated from AI include augmented transition networks, means/ends analysis, production rule systems, resolution, semantic networks, and heuristic search. Philosophers have long been interested in the question, ‘can a computer think?’ There are two schools of thought: weak AI, which is the proposition that computers can at least simulate thought and intelligence; and strong AI, which argues that a machine that can perform cognitive tasks is actually thinking. This is a complex topic that has received new interest with a focus on consciousness. Internet A discipline that attempts to replicate human skills over some domain; for example, by providing intelligent search facilities. Electronics and Electrical Engineering The study and development of computing applications for tasks that would be described as requiring intelligence if they were done by people. Many of these applications involve systems that are capable of learning, adaptation, or self-correction. Philosophy The science of making machines that can do the kinds of thing that humans can do. Topics of research have included speech recognition, visual recognition, and the more familiar problem solving and game-playing. Modelling a psychological phenomenon on a computer is a way of showing how the phenomenon is possible in a physical world, and is also a way of bringing out the complexities involved in apparently simple tasks. A central concept in much AI research is that of a representation, with programs designed to construct, adapt, and link representations in the production of intelligent responses. This research has been responsible for a considerable retreat from dogmatic behaviourism, in which the idea of mental manipulations was thought to be unscientific, since it is exactly the storage and manipulation of representations of the world that is demanded in the problems AI approaches. Strong AI is the philosophical thesis that appropriately programmed computers have minds in exactly the same sense that we do. Weak AI is the methodological belief that the best way to explore the mind is to proceed as if this were true, without commenting on the legacies of dualism that lead to discomfort with the strong thesis. See also Chinese room, connectionism, frame problem, Turing test. http://www.bbc.co.uk/radio4/history/inourtime/inourtime_20051208.shtml An audio discussion of AI by two scientists and a philosopher http://www.aaai.org/aitopics/html/welcome.html A dynamic library of internet resources on AI
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