AI-complete
In the field of
artificial intelligence, the most difficult problems are informally known as AI-complete or AI-hard, implying that the difficulty of these computational problems is equivalent to solving the central artificial intelligence problem, in other words, making computers as intelligent as people. The usage is analogous to the use of concepts such as
NP-complete and
NP-hard in
complexity theory, which formally describes the most famous class of difficult problems. John Mallery said in 1988 that the term was coined by Fanya Montalvo. Early uses of the term are in Erik Mueller's 1987 Ph.D. dissertation and in Eric Raymond's 1991 jargon file.
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IA-complet
AI-полный
AI-полный, по аналогии с
NP-полным классом задач в теории сложности, — термин, предложенный Ф. С. Монталво для обозначения того факта, что сложность компьютерной задачи эквивалентна главной проблеме
искусственного интеллекта — сделать компьютеры такими же умными, как люди. В отличие от строгого понятия NP-полноты, AI-полнота используется как неформальный термин.
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ai-complete
ai-complete
/a-i k*m-pleet'/ (mit, stanford: by analogy with "np-complete") a term used to describe problems or subproblems in artificial intelligence, to indicate that the solution presupposes a solution to the "strong ai problem" (that is, the synthesis of a human-level intelligence). a problem that is ai-complete is, in other words, just too hard.
see also gedanken.
AI-complete