all theoretically the intelligence activities are a result of feedback mechanism and feedback mechanism is. Can use machine. The findings of the simulation of early development of AI.
1955, Simon and end Newell called \program is considered by many to be the first AI programs. It will each problem is expressed as a tree, then choose the model may be correct conclusion that a problem to solve. \to the public and the AI expert research field effect makes it AI developing an important milestone in 1956, is considered to be the father of artificial intelligence of John McCarthy organized a society, will be a lot of interest machine
intelligence experts and scholars together for a month. He asked them to Vermont Dartmouth in \intelligence research in summer.\since then, this area was named \learn not very successful, but it was the founder of the centralized and AI AI research for later laid a foundation.
After the meeting of Dartmouth, AI research started seven years. Although the rapid development of field haven't define some of the ideas, meeting has been reconsidered and Carnegie Mellon university. And MIT began to build AI research center is confronted with new challenges. Research needs to establish the: more effective to solve the problem of the system, such as \establishment of the system can be self learning.
In 1957, \version was tested. This program is by the same logic \development. The GPS expanded Wiener feedback principle, can solve many common problem. Two years later, IBM has established a grind investigate group Herbert AI. Gelerneter spent three years to make a geometric theorem of solutions of the program. This achievement was a sensation.
When more and more programs, McCarthy busy emerge in the history of an AI. 1958 McCarthy announced his new fruit: LISP until today still LISP language. In. \mean\LISP list processing \it quickly adopted for most AI developers.
In 1963 MIT from the United States government got a pen is 22millions dollars funding for research funding. The machine auxiliary recognition from the defense advanced research program, have guaranteed in the technological progress on this plan ahead of the Soviet union. Attracted worldwide computer scientists, accelerate the pace of development of AI research.
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Large program
After years of program. It appeared a famous called \SHRDLU \the tiny part of the world \including the world (for example, only limited quantity of geometrical form of research and programming). In the MIT leadership of Minsky Marvin by researchers found, facing the object, the small computer programs can solve the problem space and logic. Other as in the late 1960's STUDENT\\solve algebraic problems,\SIR \handling the language understanding and logic.
In the 1970s another expert system. An expert system is a intelligent computer program system, and its internal contains a lot of certain areas of experience and knowledge with expert level, can use the human experts' knowledge and methods to solve the problems to deal with this problem domain. That is, the expert system is a specialized knowledge and experience of the program system. Progress is the expert system could predict under certain conditions, the probability of a solution for the computer already has. Great capacity, expert systems possible from the data of expert system. It is widely used in the market. Ten years, expert system used in stock, advance help doctors diagnose diseases, and determine the position of mineral instructions miners. All of this because of expert system of law and information storage capacity and become possible.
In the 1970s, a new method was used for many developing, famous as AI Minsky tectonic theory put forward David Marr. Another new theory of machine vision square, for example, how a pair of image by shadow, shape, color, texture and basic information border. Through the analysis of these images distinguish letter, can infer what might be the image in the same period. PROLOGE result is another language, in 1972. In the 1980s, the more rapid progress during the AI, and more to go into business. 1986, the AI related software and hardware sales $4.25 billion dollars. Expert system for its utility, especially by demand. Like digital electric company with such company XCON expert system for the VAX mainframe programming. Dupont, general motors and Boeing has lots of dependence of expert system for computer expert. Some production expert system of manufacture software auxiliary, such as Teknowledge and Intellicorp established. In order to find and correct the mistakes, existing expert system and some other experts system was designed，such as teach users learn TVC expert system of the operating system.
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From the lab to daily life
People began to feel the computer technique and artificial
intelligence. No influence of computer technology belong to a group of researchers in the lab. Personal computers and computer technology to numerous technical magazine now before a people. Like the United States artificial intelligence association foundation. Because of the need to develop, AI had a private company researchers into the boom. More than 150 a DEC (it employs more than 700 employees engaged in AI research) that have spent 10 billion dollars in internal AI team.
Some other AI areas in the 1980s to enter the market. One is the machine vision Marr and achievements of Minsky. Now use the camera and production, quality control computer. Although still very humble, these systems have been able to distinguish the objects and through the different shape. Until 1985 America has more than 100 companies producing machine vision systems, sales were us $8 million.
But the 1980s to AI and industrial all is not a good year for years. 1986-87 AI system requirements, the loss of industry nearly five hundred million dollars. Teknowledge like Intellicorp and two loss of more than $6 million, about one-third of the profits of the huge losses forced many research funding cuts the guide led. Another disappointing is the defense advanced research programme support of so-called \project truck purpose is to develop a can finish the task in many
battlefield robot. Since the defects and successful hopeless, Pentagon stopped project funding.
Despite these setbacks, AI is still in development of new technology slowly. In Japan were developed in the United States, such as the fuzzy logic, it can never determine the conditions of decision making, And neural network, regarded as the possible approaches to realizing artificial intelligence. Anyhow, the eighties was introduced into the market, the AI and shows the practical value. Sure, it will be the key to the 21st century. \intelligence technology acceptance inspection in desert storm\action of military intelligence test equipment through war. Artificial intelligence technology is used to display the missile system and warning and other advanced weapons. AI technology has also entered family. Intelligent computer increase attracting public interest. The emergence of network game, enriching people's life. Some of the main Macintosh and IBM for application software such as voice and character recognition has can buy, Using fuzzy logic,
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AI technology to simplify the camera equipment. The artificial intelligence technology related to promote greater demand for new progress appear constantly. In a word ，Artificial intelligence has and will continue to inevitably changed our life.
附件三 英文文献译文
人工智能
“人工智能”一词最初是在1956 年Dartmouth在学会上提出来的。从那以后,研究者们研究出了众多的理论和原理,人工智能的概念也随之得到了飞速扩展。人工智能是一门极富挑战性的科学，从事这项工作的人必须懂得计算机知识，心理学和哲学。人工智能涉及到十分广泛的科学知识，它由不同的领域组成，比如机器学习，计算机视觉等等，总的说来，人工智能研究的一个重要目标是使机器能够胜任一些通常需要人类智能才能完成的复杂工作。但在不同的时代、不同的人对这种“复杂工作”的理解是不同的。例如繁重复杂的科学和工程计算本来是要人脑来承担的，现在计算机不但能完成这种计算, 而且能够比人脑做得更效率、更准确，因此现代人已不再把这种计算看作是“需要人类智能才能完成的复杂任务”, 可见复杂工作的定义是随着时代的发展和技术的进步而变化的, 人工智能这门科学的具体目标也自然随着时代的变化而发展。它一方面不断获得新的进展，一方面又转向更有意义、更加困难的目标。目前能够用来研究人工智能的主要物理手段以及能够实现人工智能技术的机器就是计算机, 人工智能的发展历史是和计算机科学与技术的发展史联系在一起的。除了计算机科学以外, 人工智能还涉及信息论、控制论、自动化、仿生学、生物学、心理学、数理逻辑、语言学、医学和哲学等多门学科。人工智能学科研究的主要内容包括：知识表示、自动推理和搜索方法、机器学习和知识获取、知识处理系统、自然语言理解、计算机视觉、智能机器人、自动程序设计等方面。
实际应用--机器视觉:指纹识别，人脸识别，视网膜识别，虹膜识别，掌纹识别，专家系统,智能搜索，定理证明，博弈，自动程序设计，还有航天应用等。
学科范畴--人工智能是一门边沿学科，属于自然科学和社会科学的交叉。 涉及学科--哲学和认知科学，数学，神经生理学，心理学，计算机科学，信息论，控制论，不定性论和仿生学。
研究范畴--自然语言处理，知识表现，智能搜索，推理，规划，机器学习，知识获取，组合调度问题，感知问题，模式识别，逻辑程序设计，软计算，不精确和不确定的管理，人工生命，神经网络，复杂系统，遗传算法和人类思维方式。
应用领域--智能控制，机器人学，语言和图像理解，遗传编程和机器人工厂。 安全问题
目前人工智能还在研究中，但有学者认为让计算机拥有智商是很危险的，它
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