AI(Artificial Intelligence). The term "artificial intelligence" was first put forward at the Dartmouth Society in 1956. Since then, researchers have developed many theories and principles, and the concept of artificial intelligence has also expanded. Artificial intelligence is a challenging science, and people engaged in this work must understand computer knowledge, psychology and philosophy. Artificial intelligence is a very extensive science, which is composed of different fields, such as machine learning, computer vision, etc. Generally speaking, one of the main goals of artificial intelligence research is to enable machines to be competent for some complex tasks that usually require human intelligence. But different times and different people have different understandings of this "complex work". For example, heavy scientific and engineering calculations were originally undertaken by the human brain. Now computers can not only complete this calculation, but also do it faster and more accurately than the human brain. Therefore, contemporary people no longer regard this calculation as a "complex task that needs 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 goal of artificial intelligence naturally develops with the changes of the times. On the one hand, it keeps making new progress, on the other hand, it turns to more meaningful and 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 are computers, 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 many disciplines such as information theory, cybernetics, automation, bionics, biology, psychology, mathematical logic, linguistics, medicine and philosophy.
The main contents of artificial intelligence research include: knowledge representation, automatic reasoning and search methods, machine learning and knowledge acquisition, knowledge processing system, natural language understanding, computer vision, intelligent robots, automatic programming and so on.
knowledge representation is one of the basic problems of artificial intelligence, and reasoning and searching are closely related to representation methods. Commonly used knowledge representation methods include: logical representation, production representation, semantic network representation and frame representation.
Common sense naturally attracts people's attention. Many methods have been proposed, such as nonmonotonic reasoning and qualitative reasoning, to express and deal with common sense from different angles.
Automatic reasoning in problem solving is the process of using knowledge. Because there are many knowledge representation methods, there are correspondingly many reasoning methods. The reasoning process can generally be divided into deductive reasoning and non-deductive reasoning. Predicate logic is the basis of deductive reasoning. Inheritance performance reasoning under structured representation is non-deductive. Due to the need of knowledge processing, in recent years, a variety of non-deductive reasoning methods have been proposed, such as connection mechanism reasoning, analogy reasoning, example-based reasoning, deductive reasoning and restricted reasoning.
Search is a problem solving method of artificial intelligence, and the search strategy determines the priority 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 empirical knowledge. Heuristic knowledge is often represented by heuristic functions. The more fully the heuristic knowledge is used, the smaller the search space for solving problems. 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 super-large-scale search problems with millions of nodes.
machine learning is another important topic of artificial intelligence. Machine learning refers to the process of acquiring new knowledge in a certain sense of knowledge representation. According to the different learning mechanisms, there are mainly inductive learning, analytical learning, linkage mechanism learning and genetic learning.
knowledge processing system is mainly composed of knowledge base and inference engine. Knowledge base stores the knowledge needed by the system. When the amount of knowledge is large and there are many representations, the reasonable organization and management of knowledge is important. The inference engine specifies the basic methods and strategies of using knowledge when solving problems, and it is necessary to set up a database or adopt blackboard mechanism for recording results or communication in the reasoning process. If expert knowledge in a certain field (such as medical diagnosis) is stored in the knowledge base, such a knowledge system is called an expert system. In order to meet the needs of solving complex problems, a single expert system is developing into a multi-agent distributed artificial intelligence system. At this time, knowledge sharing, cooperation among agents, and the emergence and handling of contradictions will be the key issues of research.
I. the history of artificial intelligence
artificial intelligence (AI) is a challenging science, and people engaged in this work must understand computer knowledge, psychology and philosophy. Artificial intelligence includes a wide range of science, which is composed of different fields, such as machine learning, computer vision and so on. Generally speaking, the purpose of artificial intelligence is to make the computer think like a human. This is not an easy thing. If you want to make a thinking machine, you must know what thinking is, and further, what wisdom is and what its performance is. You can say that a scientist has wisdom, but you will never say that a passerby knows nothing and has no knowledge. You also dare not say that a child has no wisdom, but you dare not say that a machine has wisdom. So how can wisdom be distinguished? What we say, what we do, and our thoughts flow out of our brains like spring water, so naturally, but can machines, then what kind of machines are smart? Scientists have made cars, trains, planes, radios and so on. They imitate the functions of our body organs, but can they imitate the functions of the human brain? So far, we only know that this thing in our crown is an organ composed of billions of nerve cells. We know very little about this thing, and imitating it may be the most difficult thing in the world.
Turing, a British scientist, made a contribution to the definition of wisdom. If a machine can pass an experiment called Turing Experiment, it is intelligent. The essence of Turing Experiment is that when people can't distinguish between the behavior of a machine and the behavior of a person without looking at its appearance, the machine is intelligent. Don't think that Turing will go down in history only by making this contribution. If you study computers, you will know that for computer people, winning the Turing Award is equivalent to winning the Nobel Prize for physicists. Turing laid the foundation for the generation of computers in theory. Without his outstanding contribution, there would be no such thing in the world, let alone any network.
Scientists had hoped to make machines that could simulate human thinking long before computers appeared. In this respect, I would like to mention another outstanding mathematician, philosopher Boolean. By mathematically and accurately describing human thinking, he and other outstanding scientists laid the thinking structure and method of intelligent machines, and the logical foundation used in our computers today was founded by him.
I think anyone who has studied computer will be familiar with Boolean. Boolean algebra that we have studied is created by it. When the computer appeared, human beings began to really have a tool that can simulate human thinking. In the years to come, countless scientists worked hard for this goal. Now artificial intelligence is no longer the patent of several scientists. Almost all computer departments in universities around the world are studying this subject, and college students who study computers must also study such a course. With unremitting efforts, computers seem to have become very smart now. In the just-concluded chess competition, computers beat people, which is known to all. You may not notice that in some places, computers help people to do other jobs that originally belonged to human beings. Computers play its role for human beings with its high speed and accuracy. Artificial intelligence has always been the frontier subject of computer science, and computer programming languages and other computer software have existed because of the progress of artificial intelligence.
Now human beings have improved the computing power of computers to an unprecedented level, and artificial intelligence will also lead the tide of computer development in the next century. Now the development of artificial intelligence is not obvious because of theoretical restrictions, but it will certainly have a profound impact on our lives like today's network.
The research on artificial intelligence has been started all over the world for a long time, but the real realization of artificial intelligence starts with the birth of computers, and then it is possible for human beings to realize human intelligence with machines. The English word AI was first put forward at a meeting in 1956. After that, it developed with some scientific efforts. The progress of artificial intelligence is not as rapid as we expected, because the basic theory of artificial intelligence is not complete, and we can't essentially explain why our brain can think, what this thinking comes from, why this thinking comes into being and so on. But after decades of development, artificial intelligence is affecting people's lives with its great power.
Let's review 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 method of storing and processing information has undergone revolutionary changes. The shape of the first computer is not very good. It is fat and delicate, and it needs to work in an air-conditioned room. If you want it to handle anything, you need to reconnect the wires. This is not a labor-saving job. Rewelding thousands of wires. I think programmers are living in heaven now.
Finally, a computer that can store programs was invented in 1949. In this way, the programming program can finally be soldered, which is much better. Because programming has become very simple, the development of computer theory has finally led to the emergence of artificial intelligence theory. People can finally find a way to store information and automatically process it.
Although it seems that this new machine can realize some human intelligence now, it was not until 1951s that people linked human intelligence with this new machine. We noticed the old man with a big belly next to him. His research on feedback theory finally led him to make a conclusion that all the results of < P > human intelligence are the results of feedback, and intelligence is produced by constantly feeding back the results to the body. Our toilet is a very good example. The reason why water doesn't flow constantly is precisely because there is a device to detect the change of water level. If there is too much water, turn off the water pipe, which realizes feedback and is a negative feedback. If even the devices in our toilets can achieve feedback, then we should be able to achieve feedback with a machine, and then realize the machine form reproduction of human intelligence. This idea has a great influence on the early days of artificial intelligence.
In 1955, Shannon and others developed The Logic TheoriST program, which is a program with a tree structure. When the program is running, it searches in the tree to find the branch of the tree closest to the possible answer to get the correct answer. This program can be said to have an important position in the history of artificial intelligence, and it has brought great influence on academics and society, so that many of the methods and ideas we are using now still come from this program in the 1951s.
in p>1956, McCarthy (the man on the right), another famous scientist in the field of artificial intelligence, convened a meeting to discuss the future development direction of artificial intelligence. Since then, the name of artificial intelligence has been formally established. This conference was not a great success in the history of artificial intelligence, but it gave the founders of artificial intelligence an opportunity to communicate with each other and paved the way for the future development of artificial intelligence. After that, the focus of workers' intelligence began to be to establish a practical system that can solve problems by itself, and the system was required to have self-learning ability. In 1957, Shannon and others developed a program called General Problem Solver(GPS), which extended Wiener's feedback theory and could solve some common problems. When other scientists are trying to develop the system, the scientist on the right has made a great contribution. He created the table processing language LISP, which is still used by many artificial intelligence programs, and it has almost become synonymous with artificial intelligence. Today, LISP is still developing.
in 1963, MIT was supported by the U.S. government and the Ministry of National Defense to conduct research on artificial intelligence. The U.S. government did not do anything else, but kept the balance with the Soviet Union in the Cold War. Although this purpose was a bit explosive, its result made artificial intelligence develop greatly. Since then, many programs have attracted much attention, and MIT has developed SHRDLU. In the 1961s, the STUDENT system could solve algebra problems, while the SIR system began to understand simple English sentences. The appearance of SIR led to the emergence of a new discipline: natural language processing. The expert system that appeared in 1971s became a great progress. For the first time, it was known that computers could take the place of human experts. Due to the improvement of computer hardware performance, artificial intelligence was able to carry out a series of important activities, such as statistical analysis of data, participation in medical diagnosis and so on. As an important aspect of life, it began to change human life. Theoretically, the 1971s was also a period of great development, and computers began to have simple thinking and vision. However, in the 1971s, another artificial intelligence language, Prolog, was born, which, together with LISP, almost became an indispensable tool for artificial intelligence workers. Don't think that artificial intelligence is far away from us. It has already entered our life, fuzzy control, decision support and so on. It is the purpose of artificial intelligence to let the computer replace human beings for simple intellectual activities and liberate human beings for other more beneficial work, but I think the endless pursuit of scientific truth is the ultimate driving force.
2. Application fields of artificial intelligence
1. Problem solving.
The first major achievement of artificial intelligence is the chess-playing program. Some technologies applied in the chess-playing level, such as looking forward a few steps, break down difficult problems into some easier sub-problems and develop into basic artificial intelligence technologies such as searching and problem induction. Today's computer programs have been able to reach the championship level of all kinds of square chess and chess. However, it has not been solved, including the ability that human players have but can not be clearly expressed. Such as the ability of chess masters to gain insight into the game. Another problem is related to the original concept of the problem, which is called the choice of problem representation in artificial intelligence. People can often find some way to think about the problem, thus making the solution easier and solving the problem. So far, artificial intelligence programs have been able to know how to consider the problem they want to solve, that is, search the solution space and find a better solution.
2