数字化转型网人工智能专题
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本文为数字化转型网(szhzxw.cn）为人工智能/AI专题系列文章之一，本文讲述了人工智能/AI专题栏目文章（一）：什么是人工智能？人工智能的研究内容、人工智能的历史。
一、什么是人工智能？
人工智能（Artificial Intelligence），英文缩写为AI。它是研究、开发用于模拟、延伸和扩展人的智能的理论、方法、技术及应用系统的一门新的技术科学。
人工智能是计算机科学的一个分支，它企图了解智能的实质，并生产出一种新的能以人类智能相似的方式做出反应的智能机器，该领域的研究包括机器人、语言识别、图像识别、自然语言处理和专家系统等。人工智能从诞生以来，理论和技术日益成熟，应用领域也不断扩大，可以设想，未来人工智能带来的科技产品，将会是人类智慧的“容器”。人工智能可以对人的意识、思维的信息过程的模拟。人工智能不是人的智能，但能像人那样思考、也可能超过人的智能。
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。人工智能是包括十分广泛的科学，它由不同的领域组成，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主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。但不同的时代、不同的人对这种“复杂工作”的理解是不同的。 数字化转型网www.szhzxw.cn
2017年12月，人工智能入选“2017年度中国媒体十大流行语”。
二、人工智能的研究内容
人工智能的研究是高度技术性和专业的，各分支领域都是深入且各不相通的，因而涉及范围极广。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。
1）知识表示是人工智能的基本问题之一，推理和搜索都与表示方法密切相关。常用的知识表示方法有：逻辑表示法、产生式表示法、语义网络表示法和框架表示法等。
2）常识，自然为人们所关注，已提出多种方法，如非单调推理、定性推理就是从不同角度来表达常识和处理常识的。 数字化转型网www.szhzxw.cn
3）问题求解中的自动推理是知识的使用过程，由于有多种知识表示方法，相应地有多种推理方法。推理过程一般可分为演绎推理和非演绎推理。谓词逻辑是演绎推理的基础。结构化表示下的继承性能推理是非演绎性的。由于知识处理的需要，近几年来提出了多种非演泽的推理方法，如连接机制推理、类比推理、基于示例的推理、反绎推理和受限推理等。
4）搜索是人工智能的一种问题求解方法，搜索策略决定着问题求解的一个推理步骤中知识被使用的优先关系。可分为无信息导引的盲目搜索和利用经验知识导引的启发式搜索。启发式知识常由启发式函数来表示，启发式知识利用得越充分，求解问题的搜索空间就越小。典型的启发式搜索方法有A*、AO*算法等。近几年搜索方法研究开始注意那些具有百万节点的超大规模的搜索问题。
5）机器学习是人工智能的另一重要课题。机器学习是指在一定的知识表示意义下获取新知识的过程，按照学习机制的不同，主要有归纳学习、分析学习、连接机制学习和遗传学习等。
6）知识处理系统主要由知识库和推理机组成。知识库存储系统所需要的知识，当知识量较大而又有多种表示方法时，知识的合理组织与管理是重要的。推理机在问题求解时，规定使用知识的基本方法和策略，推理过程中为记录结果或通信需设数据库或采用黑板机制。如果在知识库中存储的是某一领域(如医疗诊断)的专家知识，则这样的知识系统称为专家系统。为适应复杂问题的求解需要，单一的专家系统向多主体的分布式人工智能系统发展，这时知识共享、主体间的协作、矛盾的出现和处理将是研究的关键问题。
人工智能的研究可以分为几个技术问题。其分支领域主要集中在解决具体问题，其中之一是，如何使用各种不同的工具完成特定的应用程序。AI的核心问题包括推理、知识、规划、学习、交流、感知、移动和操作物体的能力等。强人工智能目前仍然是该领域的长远目标。目前比较流行的方法包括统计方法，计算智能和传统意义的AI。目前有大量的工具应用了人工智能，其中包括搜索和数学优化、逻辑推演。而基于仿生学、认知心理学，以及基于概率论和经济学的算法等等也在逐步探索当中。
三、人工智能的历史
“人工智能”一词最初是在1956年达特茅斯（Dartmouth）学会上提出的。从那以后，研究者们发展了众多理论和原理，人工智能的概念也随之扩展。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。人工智能是包括十分广泛的科学，它由不同的领域组成，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主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快、更准确, 因之当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质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。 数字化转型网www.szhzxw.cn
在定义智慧时，英国科学家图灵做出了贡献，如果一台机器能够通过称之为图灵实验的实验，那它就是智慧的，图灵实验的本质就是让人在不看外型的情况下不能区别是机器的行为还是人的行为时，这个机器就是智慧的。不要以为图灵只做出这一点贡献就会名垂表史，如果你是学计算机的就会知道，对于计算机人士而言，获得图灵奖就等于物理学家获得诺贝尔奖一样，图灵在理论上奠定了计算机产生的基础，没有他的杰出贡献世界上根本不可能有这个东西，更不用说什么网络了。
科学家早在计算机出现之前就已经希望能够制造出可能模拟人类思维的机器了，在这方面我希望提到另外一个杰出的数学家、哲学家布尔，通过对人类思维进行数学化精确地刻画，他和其它杰出的科学家一起奠定了智慧机器的思维结构与方法，今天我们的计算机内使用的逻辑基础正是他所创立的。
我想任何学过计算机的人对布尔一定不会陌生，我们所学的布尔代数，就是由它开创的。当计算机出现后，人类开始真正有了一个可以模拟人类思维的工具了，在以后的岁月中，无数科学家为这个目标努力着，现在人工智能已经不再是几个科学家的专利了，全世界几乎所有大学的计算机系都有人在研究这门学科，学习计算机的大学生也必须学习这样一门课程，在大家不懈的努力下，现在计算机似乎已经变得十分聪明了，刚刚结束的国际象棋大赛中，计算机把人给胜了，这是人们都知道的，大家或许不会注意到，在一些地方计算机帮助人进行其它原来只属于人类的工作，计算机以它的高速和准确为人类发挥着它的作用。人工智能始终是计算机科学的前沿学科，计算机编程语言和其它计算机软件都因为有了人工智能的进展而得以存在。
现在人类已经把计算机的计算能力提高到了前所未有的地步，而人工智能也在下世纪领导计算机发展的潮头，现在人工智能的发展因为受到理论上的限制不是很明显，但它必将象今天的网络一样深远地影响我们的生活。 数字化转型网www.szhzxw.cn
让我们顺着人工智能的发展来回顾一下计算机的发展，在1941年由美国和德国两国共同研制的第一台计算机诞生了，从此以后人类存储和处理信息的方法开始发生革命性的变化。第一台计算机的体型可不算太好，它比较胖，还比较娇气，需要工作在有空调的房间里，如果希望它处理什么事情，需要大家把线路重新接一次，这可不是一件省力气的活儿，把成千上万的线重新焊一下我想现在的程序员已经是生活在天堂中了。
终于在1949发明了可以存储程序的计算机，这样，编程程序总算可以不用焊了，好多了。因为编程变得十分简单，计算机理论的发展终于导致了人工智能理论的产生。人们总算可以找到一个存储信息和自动处理信息的方法了。 数字化转型网www.szhzxw.cn
虽然现在看来这种新机器已经可以实现部分人类的智力，但是直到50年代人们才把人类智力和这种新机器联系起来。美籍俄裔数学家、控制论的创始人诺伯特·维纳（Norbert Wiener）在反馈理论上的研究最终让他提出了一个论断，所有人类智力的结果都是一种反馈的结果，通过不断地将结果反馈给机体而产生的动作，进而产生了智能。我们家的抽水马桶就是一个十分好的例子，水之所以不会常流不断，正是因为有一个装置在检测水位的变化，如果水太多了，就把水管给关了，这就实现了反馈，是一种负反馈。如果连我们厕所里的装置都可以实现反馈了，那我们应该可以用一种机器实现反馈，进而实现人类智力的机器形式重现。这种想法对于人工智能早期的有着重大的影响。
在1955的时候，美国计算机科学家艾伦·纽威尔(Allen Newell)和赫伯特·西蒙(Herbert A.Simon)The Logic Theorist程序，它是一种采用树形结构的程序，在程序运行时，它在树中搜索，寻找与可能答案最接近的树的分枝进行探索，以得到正确的答案。这个程序在人工智能的历史上可以说是有重要地位的，它在学术上和社会上带来的巨大的影响，以至于我们现在所采用的方法思想方法有许多还是来自于这个50年代的程序。 数字化转型网www.szhzxw.cn
1956年，“人工智能之父”和LISP语言的发明人(ZT) 约翰·麦卡锡（John McCarthy）召集了一次会议来讨论人工智能未来的发展方向。从那时起，人工智能的名字才正式确立，这次会议在人工智能历史上不是巨大的成功，但是这次会议给人工智能奠基人相互交流的机会，并为未来人工智能的发展起了铺垫的作用。在此以后，工人智能的重点开始变为建立实用的能够自行解决问题的系统，并要求系统有自学习能力。在1957年，艾伦·纽威尔和赫伯特·西蒙又开发了一个程序称为General Problem Solver(GPS)，它对维纳的反馈理论有一个扩展，并能够解决一些比较普遍的问题。别的科学家在努力开发系统时，麦卡锡创建了表处理语言LISP，直到现在许多人工智能程序还在使用这种语言，它几乎成了人工智能的代名词，到了今天，LISP仍然在发展。
在1963年，麻省理工学院受到了美国政府和国防部的支持进行人工智能的研究，美国政府不是为了别的，而是为了在冷战中保持与苏联的均衡，虽然这个目的是带点火药味的，但是它的结果却使人工智能得到了巨大的发展。其后发展出的许多程序十分引人注目，SHRDLU是维诺格拉德(T.Winograd)于1972年在美国麻省理工学院建立了一个用自然语言指挥机器人动作的系统。在这个大发展的60年代，STUDENT系统可以解决代数问题，而SIR(Selective Integrated Rail)系统则开始理解简单的英文句子了，SIR的出现导致了新学科的出现：自然语言处理。在70年代出现的专家系统成了一个巨大的进步，他头一次让人知道计算机可以代替人类专家进行一些工作了，由于计算机硬件性能的提高，人工智能得以进行一系列重要的活动，如统计分析数据，参与医疗诊断等等，它作为生活的重要方面开始改变人类生活了。在理论方面，70年代也是大发展的一个时期，计算机开始有了简单的思维和视觉，而不能不提的是在70年代，另一个人工智能语言Prolog语言诞生了，它和LISP一起几乎成了人工智能工作者不可缺少的工具。不要以为人工智能离我们很远，它已经在进入我们的生活，模糊控制，决策支持等等方面都有人工智能的影子。让计算机这个机器代替人类进行简单的智力活动，把人类解放用于其它更有益的工作，这是人工智能的目的，但我想对科学真理的无尽追求才是最终的动力吧。 数字化转型网www.szhzxw.cn
数字化转型网人工智能专题
与全球关注人工智能的顶尖精英一起学习！数字化转型网建立了一个专门讨论人工智能技术、产业、学术的研究学习社区，与各位研习社同学一起成长！欢迎扫码加入！ 数字化转型网www.szhzxw.cn
人工智能专题栏目文章（一）：人工智能/AI专题栏目文章（一）：什么是人工智能？人工智能的研究内容、人工智能的历史。翻译：
Artificial Intelligence /AI Special column Article (1) : What is Artificial Intelligence? Research content of artificial intelligence, history of artificial intelligence.
1. What is artificial intelligence?
Artificial Intelligence (AI). It is a new technical science to study and develop the theory, method, technology and application system for simulating, extending and expanding human intelligence.
Artificial intelligence is a branch of computer science that attempts to understand the nature of intelligence and produce a new kind of intelligent machine that can react in a similar way to human intelligence. Research in this field includes robotics, speech recognition, image recognition, natural language processing, and expert systems. Since the birth of artificial intelligence, the theory and technology are increasingly mature, and the application field is also expanding, it can be imagined that the scientific and technological products brought by artificial intelligence in the future will be the “container” of human wisdom. Artificial intelligence can simulate the information process of human consciousness and thinking. Artificial intelligence is not human intelligence, but can think like a human, and may exceed human intelligence. 数字化转型网www.szhzxw.cn
Artificial intelligence is a very challenging science, and those who do it must have knowledge of computers, psychology, and philosophy. Artificial intelligence is a very broad science, it is composed of different fields, such as machine learning, computer vision, etc. In general, one of the main goals of artificial intelligence research is to make machines capable of some complex tasks that usually require human intelligence to complete. But different times, different people’s understanding of this “complex work” is different. 数字化转型网www.szhzxw.cn
In December 2017, artificial intelligence was selected as one of the “Top ten buzzwords in Chinese media in 2017”. 数字化转型网www.szhzxw.cn
2. The research content of artificial intelligence
The research of artificial intelligence is highly technical and professional, and each branch field is deep and different, so it involves a very wide range. The main research contents of artificial intelligence include: knowledge representation, automatic reasoning and search methods, machine learning and knowledge acquisition, knowledge processing system, natural language understanding, computer vision, intelligent robot, automatic programming and so on.
1) Knowledge representation is one of the fundamental problems of artificial intelligence, and inference and search are closely related to representation methods. The common knowledge representation methods include logical representation, production representation, semantic network representation and frame representation.
2) Common sense, naturally concerned by people, has proposed a variety of methods, such as non-monotonic reasoning, qualitative reasoning is from different angles to express common sense and deal with common sense. 数字化转型网www.szhzxw.cn
3) Automatic reasoning in problem solving is the process of using knowledge, because there are a variety of knowledge representation methods, there are correspondingly a variety of reasoning methods. The reasoning process can be divided into deductive reasoning and non-deductive reasoning. Predicate logic is the basis of deductive reasoning. Inheritance performance inference under structured representation is non-deductive. Due to the need of knowledge processing, a variety of non-reductive reasoning methods have been proposed in recent years, such as connection-mechanism reasoning, analogical reasoning, example-based reasoning, inverse reasoning and limited reasoning.
4) Search is a problem solving method of artificial intelligence, and the search strategy determines the priority relationship of knowledge used in a reasoning step of problem solving. It can be divided into blind search without information guidance and heuristic search guided by experience knowledge. Heuristic knowledge is often represented by a heuristic function, and the more fully the heuristic knowledge is used, the smaller the search space for solving the problem. Typical heuristic search methods include A, AO algorithm and so on. In recent years, the research of search methods has begun to pay attention to those with millions of nodes of very large scale search problems.
5) Machine learning is another important topic in artificial intelligence. Machine learning refers to the process of acquiring new knowledge in a certain sense of knowledge representation. According to different learning mechanisms, it mainly includes inductive learning, analytical learning, connection-mechanism learning and genetic learning. 数字化转型网www.szhzxw.cn
6) Knowledge processing system is mainly composed of knowledge base and inference unit. It is important to organize and manage knowledge reasonably when the amount of knowledge is large and there are many ways to express it. Inference machine specifies the basic methods and strategies of using knowledge when solving problems. In the process of inference, database or blackboard mechanism is needed to record results or communicate. If the knowledge base stores expert knowledge in a certain field (such as medical diagnosis), such a knowledge system is called an expert system. In order to meet the needs of solving complex problems, a single expert system develops into a multi-agent distributed artificial intelligence system. At this time, knowledge sharing, inter-agent cooperation, the emergence and treatment of contradictions will be the key issues of research.
The study of artificial intelligence can be divided into several technical issues. Its sub-areas focus on solving specific problems, one of which is how to use a variety of different tools to complete a particular application. The core problems of AI include reasoning, knowledge, planning, learning, communication, perception, the ability to move and manipulate objects. Strong artificial intelligence is still the long-term goal in this field. Popular methods include statistical methods, computational intelligence, and AI in the traditional sense. There are a large number of tools that apply AI, including search and mathematical optimization, and logic inference. Algorithms based on bionics, cognitive psychology, and probability theory and economics are also being gradually explored.
3. History of artificial intelligence
The term “artificial intelligence” was first coined at the Dartmouth Society meeting in 1956. Since then, researchers have developed numerous theories and principles, and the concept of artificial intelligence has expanded. Artificial intelligence is a very challenging science, and those who do it must have knowledge of computers, psychology, and philosophy. Artificial intelligence is a very broad science, it is composed of different fields, such as machine learning, computer vision, etc. In general, one of the main goals of artificial intelligence research is to make machines capable of some complex tasks that usually require human intelligence to complete. But different times, different people’s understanding of this “complex work” is different. For example, heavy scientific and engineering calculations were originally to be undertaken by the human brain, but now the computer can not only complete such calculations, but also do them faster and more accurately than the human brain, so the contemporary people no longer regard such calculations as “complex tasks that require human intelligence to complete”. It can be seen that the definition of complex work changes with the development of The Times and the progress of technology, and the specific goals of the science of artificial intelligence also naturally develop with the changes of The Times. On the one hand, it is constantly making new progress, on the other hand, it is moving to more meaningful and more difficult goals. At present, the main material means that can be used to study artificial intelligence and the machine that can realize artificial intelligence technology is the computer, and the development history of artificial intelligence is linked with the development history of computer science and technology. In addition to computer science, artificial intelligence also involves information theory, cybernetics, automation, bionics, biology, psychology, mathematical logic, linguistics, medicine and philosophy. 数字化转型网www.szhzxw.cn
In defining intelligence, the British scientist Alan Turing made a contribution. A machine is intelligent if it can pass an experiment called Turing’s experiment. The essence of Turing’s experiment is that a person cannot distinguish between a machine’s behavior and a person’s behavior without looking at the appearance of the machine. Do not think that Turing only made this contribution will be famous history, if you are studying computer will know that for computer people, winning the Turing Award is equivalent to physicists winning the Nobel Prize, Turing in theory laid the basis for the production of computers, without his outstanding contribution to the world is impossible to have this thing, let alone what the network. 数字化转型网www.szhzxw.cn
Scientists long before the advent of computers have hoped to build machines that could simulate human thinking. In this regard, I would like to mention another outstanding mathematician and philosopher, Boole, who, together with other outstanding scientists, laid down the thinking structure and methods of intelligent machines through the mathematical and precise characterization of human thinking. It was he who created the logic that is used in our computers today.
I think that anyone who has studied computers will be familiar with Boolean, which is the beginning of the Boolean algebra that we learn. When the computer appeared, human beings began to really have a tool that can simulate human thinking, in the later years, countless scientists are working hard for this goal, and now artificial intelligence is no longer the patent of a few scientists, almost all the computer departments of universities in the world have people studying this subject, and college students who learn computer must also learn such a course. With everyone’s unremitting efforts, now the computer seems to have become very smart, just ended in the chess competition, the computer won people, this is known to everyone, you may not notice, in some places the computer to help people to carry out other work originally only belong to human, computer with its high speed and accuracy for human play its role. Artificial intelligence has always been the frontier of computer science, and computer programming languages and other computer software have come into existence because of advances in artificial intelligence. 数字化转型网www.szhzxw.cn
Now human beings have increased the computing power of computers to an unprecedented level, and artificial intelligence will lead the development of computers in the next century, the development of artificial intelligence is not obvious because of theoretical limitations, but it will certainly have as profound an impact on our lives as today’s network.
Let’s look back at the development of computers along with the development of artificial intelligence. In 1941, the first computer jointly developed by the United States and Germany was born, and since then, the way humans store and process information has undergone revolutionary changes. The body of the first computer is not too good, it is fat, but also more delicate, need to work in an air-conditioned room, if you want it to deal with anything, you need to reconnect the line once again, this is not a energy-saving job, thousands of lines to re-weld I think the programmer is now living in paradise.
Finally in 1949, the invention of a computer that can store programs, so that programming programs can finally be welded, much better. Because programming became so easy, the development of computer theory eventually led to the creation of artificial intelligence theory. People can finally find a way to store information and automatically process it. 数字化转型网www.szhzxw.cn
Although it now seems that this new machine can realize part of human intelligence, it was not until the 1950s that people connected human intelligence to this new machine. Norbert Wiener, a Russian-born mathematician and the founder of cybernetics, whose work on feedback theory eventually led him to conclude that all the results of human intelligence are the result of feedback, and that intelligence is produced by actions that constantly feed the results back to the body. The toilet bowl in our home is a very good example, the reason why the water does not flow constantly is because there is a device to detect the change in the water level, if there is too much water, the pipe is turned off, which is a feedback, a negative feedback. If even the devices in our toilets can give feedback, then we should be able to use a machine to give feedback, and thus achieve a mechanical reproduction of human intelligence. This idea had a major impact on the early days of artificial intelligence.
In 1955, American computer scientists Allen Newell and Herbert A.Simon developed The Logic Theorist program, which is a program that adopts a tree structure. When the program is running, it searches in the tree. Look for the branch of the tree closest to the possible answer and explore to get the right answer. This program can be said to have an important place in the history of artificial intelligence, and it has brought a huge impact on academia and society, so that many of the methods and ideas we use today are still from this program in the 1950s. 数字化转型网www.szhzxw.cn
In 1956, John McCarthy, the “father of artificial intelligence” and inventor of the LISP language (ZT), called a conference to discuss the future direction of artificial intelligence. Since then, the name of artificial intelligence has been formally established, and the conference was not a great success in the history of artificial intelligence, but the conference gave the founders of artificial intelligence the opportunity to communicate with each other and paved the way for the future development of artificial intelligence. After this, the emphasis on worker intelligence began to be on building practical systems that could solve problems on their own, and required the system to have the ability to learn. In 1957, Alan Newell and Herbert Simon developed a program called General Problem Solver(GPS), which extended Wiener’s feedback theory and was able to solve some of the more general problems. While other scientists struggled to develop the system, McCarthy created the list-processing language LISP, which is still used by many artificial intelligence programs today, has become almost synonymous with artificial intelligence, and is still being developed today. 数字化转型网www.szhzxw.cn
In 1963, MIT was supported by the United States government and the Department of Defense to conduct artificial intelligence research, the United States government is not for anything else, but to maintain the balance with the Soviet Union in the Cold War, although this purpose is a little explosive, but its result has made a huge development of artificial intelligence. Many of the programs that have evolved since then have been notable. SHRDLU was created by T.Winograd in 1972 at the Massachusetts Institute of Technology in the United States to direct the actions of robots in natural language. In the 1960s, the STUDENT system could solve algebra problems, and the Selective Integrated Rail (SIR) system began to understand simple English sentences, and the emergence of SIR Led to the emergence of a new discipline: natural language processing. The emergence of expert system in the 1970s became a great progress, he let people know for the first time that computers can replace human experts to do some work, because of the improvement of computer hardware performance, artificial intelligence can carry out a series of important activities, such as statistical analysis of data, participate in medical diagnosis and so on, it as an important aspect of life began to change human life. In terms of theory, the 1970s was also a period of great development, computers began to have simple thinking and vision, and it cannot be mentioned that in the 1970s, another artificial intelligence language Prolog language was born, which together with LISP almost became an indispensable tool for artificial intelligence workers. Do not think that artificial intelligence is far away from us, it has entered our lives, fuzzy control, decision support and so on have the shadow of artificial intelligence. Let the computer this machine to replace the human to carry out simple intellectual activities, the human liberation for other more beneficial work, this is the purpose of artificial intelligence, but I think the endless pursuit of scientific truth is the ultimate driving force. 数字化转型网www.szhzxw.cn
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