What is artificial intelligence? History of development and prospects. The main directions of research

The buildings 20.09.2019

The buildings

Indicates: "The problem is that while we cannot generally determine which computational procedures we want to call intellectual. We understand some intelligence mechanisms and do not understand the rest. Therefore, under the intellect within this science, only the computing component of the ability to achieve goals in the world is understood. "

At the same time, there is also a point of view according to which intelligence can only be a biological phenomenon.

As indicated by the chairman of the St. Petersburg branch of the Russian Association of Artificial Intelligence, T. A. Gavrilova, english language phrase aRTIFICIAL INTELLIGENCE It does not have the slightly fantastic anthropomorphic color, which it has acquired in a rather unsuccessful Russian translation. Word intelligence means "ability to reason intelligent", and not at all "intelligence" for which there is English analog intellect. .

Participants in the Russian Association of Artificial Intelligence give the following definitions of artificial intelligence:

One of the private definitions of intelligence, common to humans and "machines", can be formulated as follows: "Intellect - the ability of the system to create during the self-learning of the program (first of all heuristic) to solve the tasks of a certain class of complexity and solve these tasks."

Often, artificial intelligence is also called the simplest electronics to indicate the presence of sensors and automatic choice Work modes. The word artificial in this case means that you should not expect from the skill system to find new regime Work in the situation not provided for by developers.

Artificial Intelligence Science Development Backgrounds

The history of artificial intelligence as a new scientific direction begins in the middle of the 20th century. By this time, many prerequisites for its origin have already been formed: the philosophers have long been disputes about the nature of the person and the process of knowledge of the world, neurophysiologists and psychologists have developed a number of theories regarding the work of the human brain and thinking, economists and mathematicians asked for optimal calculations and presentation of knowledge about the world in formalized form; Finally, the foundation originated mathematical theory Computations - theory of algorithms - and the first computers were created.

The possibilities of new cars in terms of calculation speed were more human, so the question of which the boundaries of the capabilities of the computers were crying and did the road opportunities of the person achieved? In 1950, one of the pioneers in the field of computing equipment, an English scientist Alan Turing, writes an article entitled "Can the car think?" which describes the procedure with which it will be possible to determine the moment when the machine is equal in terms of intelligence with a person called the Turing test.

The history of the development of artificial intelligence in the USSR and Russia

In 1964, the work of the Leningrad Logic of Sergey Maslov was published " Reverse method The establishment of predicate-based predicate is determined, in which the method of automatic search for proof by theorems in the predicate calculation was presented for the first time.

Until the 1970s, all studies have been conducted in the USSR in the framework of cybernetics. According to D. A. Pospelova, the science of "Informatics" and "Cybernetics" was mixed at this time, due to a number of academic disputes. Only in the late 1970s in the USSR begin to talk about the scientific direction " artificial Intelligence"As a section of computer science. At the same time, the informatics itself was born, subdued to the PREDITER "Cybernetics". In the late 1970s it is created dictionary on artificial intelligence, trotter reference book for artificial intelligence and encyclopedic Dictionary According to the computer science, in which the sections "Cybernetics" and "artificial intelligence" are included along with other sections in computer science. The term "Informatics" in the 1980s is widespread, and the term "cybernetics" gradually disappears from the appeal, preserved only in the names of those institutions that arose in the era of the "cybernetic boom" of the late 1950s - early 1960s. Such a look at artificial intelligence, cybernetics and computer science is not divided by everyone. This is due to the fact that in the West borders of these sciences are somewhat different.

Approaches and directions

Approaches to understanding the problem

A single answer to the question than the artificial intelligence does not exist. Almost every author, writing a book about AI, is repelled in it from any definition, considering in its light to achieve this science.

downward (eng. TOP-DOWN AI), semiotic - the creation of expert systems, knowledge bases and logical conclusions, imitating high-level mental processes: thinking, reasoning, speech, emotions, creativity, etc.;
ascending (eng. Bottom-Up AI), biological - study of neural networks and evolutionary calculations that simulate intelligent behavior based on biological elements, as well as the creation of appropriate computing systems, such as a neurocomputer or biocomputer.

The last approach, strictly speaking, does not apply to the science of AI in the sense of this John McCarthy, - they are united only by the general ultimate goal.

Turing Turing and an intuitive approach

The empirical test was proposed by Alan Turing in the article "Computing Machines and Mind" (Eng. Computing Machinery and Intelligence ), published in 1950 in the philosophical journal " Mind." The purpose of this test is to determine the possibility of artificial thinking close to human.

The standard interpretation of this test sounds as follows: " A person interacts with one computer and one person. Based on answers to questions, he must determine who he is talking to: with a person or computer program. The task of a computer program - to enter a person in misleading, forcing the wrong choice" All dough participants do not see each other.

The most general approach suggests that the AI \u200b\u200bwill be able to show behavior that does not differ from human, and in normal situations. This idea is a generalization of the Turing test approach, which claims that the car will be reasonable when it is able to maintain a conversation with an ordinary person, and he will not be able to understand what he speaks with the car (talking on correspondence).
Science fiction writers often offer another approach: AI will arise when the car will be able to feel and create. So, the owner Andrew Martina from the "Two-Year-Year Man" begins to treat him as a person when he creates a toy on his own project. And the diet from the star road, being able to communicate and learned, dreams of gaining emotions and intuition.

However, the last approach is unlikely to stand criticism at more detailed consideration. For example, it is easy to create a mechanism that will evaluate some parameters of the external or internal environment and respond to their adverse values. We can say about such a system that it has feelings ("pain" - a reaction to the triggering of the impact sensor, "hunger" is a reaction to a low battery charge, etc.). And clusters created by Kohonen cards, and many other "intelligent" systems can be considered as a type of creativity.

Symbolic approach

Historically, the symbol approach was the first in the era of digital machines, since it was after the creation of a Lisp, the first language of symbolic computing, his author had confidence in the ability to practically proceed to implement these means of intelligence. The symbol approach allows to operate with weakly informal presentations and their meanings.

The success and efficiency of solving new tasks depends on the ability to allocate only substantial information, which requires flexibility in abstraction methods. Then the usual program establishes one of its way of interpretation of the data, which is why it works and looks biased and purely mechanical. In this case, the intellectual task in this case solves only a person, an analyst or programmer, without knowing how to trust this car. As a result, a single abstraction model is created, a system of constructive entities and algorithms. And flexibility and versatility poured into significant costs of resources for non-typical tasks, that is, the system from intelligence returns to rough strength.

The main feature of symbolic calculations is the creation of new rules in the process of executing the program. Whereas the possibilities of non-intelligent systems are completed just before the ability to at least designate newly emerging difficulties. Moreover, these difficulties are not solved and finally the computer does not improve such abilities independently.

The disadvantage of the symbolic approach is that such open opportunities are perceived by non-trained people as the lack of instruments. This, rather cultural problem, partly solves logical programming.

Logic approach

A logical approach to creating artificial intelligence systems is aimed at creating expert systems with logical knowledge base models using predicate language.

The training model of artificial intelligence systems in the 1980s was adopted by the language and system of logical programming Prolog. Knowledge bases recorded in the Prologue language represent the sets of facts and rules of the logical conclusion recorded in the language of logical predicates.

The logical model of the knowledge base allows you to record not only specific information and data in the form of facts in the Prologue language, but also generalized information using the rules and procedures of the logical conclusion, and including the logical rules for determining the concepts expressing certain knowledge as specific and summarized information.

In general, the study of the problems of artificial intelligence as part of a logical approach to the design of knowledge bases and expert systems is aimed at creating, developing and operating intellectual information systems, including learning students and schoolchildren, as well as training users and developers of such intelligent information systems.

Agent-oriented approach

The last approach developed since the early 1990s is called an agent-oriented approach, or approach based on the use of intellectual (rational) agents. According to this approach, intelligence is a computing part (roughly speaking, planning) the ability to achieve the goals set before the intellectual machine. This machine itself will be an intelligent agent that perceives the world around him with the help of sensors, and capable of influencing objects in environment With the help of executive mechanisms.

This approach emphasizes attention on those methods and algorithms that will help the intellectual agent to survive in the environment when performing its task. So, here is much more carefully studied the search algorithms and decision-making algorithms.

Hybrid approach

Main article: Hybrid approach

Hybrid approach assumes that only The synergistic combination of neural and symbolic models reaches a complete spectrum of cognitive and computational capabilities. For example, expert rules of conclusions can be generated by neural networks, and the generating rules are obtained by statistical training. Supporters of this approach believe that hybrid information systems will be significantly stronger than the sum of various concepts separately.

Models and research methods

Symbolic modeling of mental processes

Main article: Modeling reasoning

Analyzing the history of AI, you can allocate such an extensive direction as modeling reasoning. For many years, the development of this science was moving on this path, and now it is one of the most developed areas in modern AI. The modeling of reasoning implies the creation of symbolic systems, at the entrance of which a certain task is set, and its solution requires its solution. As a rule, the proposed task is already formalized, that is, translated into a mathematical form, but either does not have a solution algorithm, or it is too complicated, laboriousness, etc. This direction includes: proof of theorems, decision making and game theory, planning and dispatching, prediction.

Work with natural languages

An important direction is treatment natural language In which the analysis of the possibilities of understanding, processing and generating texts on the "human" language is carried out. As part of this direction, the goal of such a natural language processing is set, which would be able to acquire knowledge independently, reading the existing text available on the Internet. Some direct applications of natural language processing include information search (including deep text analysis) and machine translation.

Presentation and use of knowledge

Direction engineering knowledge Combines the tasks of obtaining knowledge from simple information, their systematization and use. This direction is historically connected with the creation expert systems - programs using specialized knowledge bases to obtain reliable conclusions on any problem.

Production of knowledge from the data is one of the basic problems of intelligent data analysis. There are various approaches to solving this problem, including - based on neural network technology using neural network verbalization procedures.

Machine learning

Problems machine learning concerns the process self obtaining knowledge of the intellectual system in the process of its work. This direction was central from the very beginning of the development of AI. In 1956, at the Dartmund Summer Conference, Rei Solomonoff wrote a report on a probabilistic machine, who studies without a teacher, calling it: "Inductive output machine."

Robotics

Main article: Intellectual robotics

Machinerary creativity

Main article: Machinerary creativity

The nature of human creativity is even less studied than the nature of intelligence. Nevertheless, this area exists, and the problems of writing music, literary works (often - poems or fairy tales), artistic creativity. Creating realistic images is widely used in movies and games industry.

Separately, the study of the problems of technical creativity of artificial intelligence systems. The theory of solutions of inventive tasks, proposed in 1946 G. S. Altshuller, marked the beginning of such research.

Adding this opportunity to any intelligent system allows you to very clearly demonstrate that it is the system that is perceived and how it understands. By adding noise instead of missing information or filtering noise available in the knowledge system produces specific images that are easily perceived by a person, it is especially useful for intuitive and low-value knowledge, the test of which in the formal form requires significant mental effort.

Other research areas

Finally, there are a lot of applications of artificial intelligence, each of which forms an almost independent direction. As examples, you can cite the intelligence programming in computer games, nonlinear control, intelligent information security systems.

It can be noted that many areas of studies intersect. It is typical for any science. But in the artificial intelligence, the relationship between, it would seem, various directions are expressed particularly strongly, and this is due to the philosophical dispute about the strong and weak AI.

Modern artificial intellect

You can allocate two directions of development AI:

solving problems related to the approach to the specialized systems of the AI \u200b\u200bto human capabilities, and their integration, which is implemented by the nature of man ( see Intellect Strengthening);
the creation of an artificial mind representing the integration of already created II systems into a single system capable of solving the problems of humanity ( see strong and weak artificial intelligence).

But at the moment in the field of artificial intelligence, there is an involvement of many subject areas with rather practical attitude To the AI, not fundamental. Many approaches were tested, but to the emergence of an artificial mind, no research group has yet come true. Below are only some of the most famous developments in the field of AI.

Application

Tournament Robocup.

Some of the most famous II systems:

Banks use artificial intelligence systems (SII) in insurance activities (actuarial mathematics), when playing the stock exchange and property management. Methods of recognition of images (including more complex and specialized and neural networks) It is widely used in optical and acoustic recognition (including text and speech), medical diagnostics, spam filters, in air defense systems (definition of goals), as well as to provide a number of other national security tasks.

Psychology and Cognitology

The methodology for cognitive modeling is intended for analysis and decision-making in poorly defined situations. Was proposed by Axelrod.

Based on the modeling of subjective presentations of experts on the situation and includes: a methodology for structuring the situation: a model of representing the expert's knowledge in the form of a sign orgraf (cognitive card) (F, W), where F is a set of factors of the situation, W is a set of causal relationships between the situation factors ; Methods for analyzing the situation. Currently, the methodology for cognitive modeling is developing in the direction of improving the analysis and simulation of the situation. Here are proposed models for the development of the situation; Methods for solving inverse problems.

Philosophy

The science "On the creation of an artificial mind" could not not attract the attention of philosophers. With the advent of the first intelligent systems, fundamental questions about man and knowledge were affected, and partly about the world order.

The philosophical problems of creating artificial intelligence can be divided into two groups, relatively speaking, "before and after the development of AI." The first group answers the question: "What is AI, is it possible to create, and, if possible, how to do it?" The second group (ethics of artificial intelligence) is set as a question: "What are the consequences of creating AI for humanity?"

The term "strong artificial intelligence" introduced John Stewl, his own words approach and characterized:

Moreover, such a program will not be just a model of mind; She in the literal sense of the word herself will be mind, in the same sense in which the human mind is a mind.

At the same time, it is necessary to understand whether the "clean artificial" mind is possible ("Methahry"), which understands the decisive real problems and, at the same time, devoid of emotions characteristic of humans and necessary for its individual survival.

On the contrary, supporters of weak AI prefer to consider programs only as a tool that allows you to solve certain tasks that do not require a complete spectrum of human cognitive abilities.

Ethics

Science fiction

The topic of the AI \u200b\u200bis considered at different angles in the work of Robert Khainlanine: the hypothesis of the emergence of self-awareness of the AI \u200b\u200bwith the complication of the structure further a certain critical level and the availability of interaction with the world and other media of the mind ("The Moon Is A Harsh Mistress", "Time Enough for Love", characters Maikroft, Dora and Aya in the "History of the Future" cycle), Problems of Development of AI after hypothetical self-awareness and some social and ethical issues ("Friday"). Socio-psychological problems of the interaction of a person with AI considers and Roman Philip K. Dick "Does the Androids dreams? "Also known on the film running on the blade."

In the work of science and philosophy Stanislav Lema described and largely anticipated virtual reality, artificial intelligence, nanorobots and many other problems of artificial intelligence philosophy. It is especially worth noting the futurology of the amount of technology. In addition, in the adventures of Jione, living beings and machines are repeatedly described: the riot of onboard computer followed unexpected events (11 journey), adaptation of robots in human society ("Washing tragedy" from "Iyon's memories"), building an absolute order on the planet by processing living inhabitants (24th journey), the inventions of the crocoon and the diagnostic ("Memonies of the Quiet"), a psychiatric clinic for robots ("Memonies of the Quiet "). In addition, there is a whole cycle of the ages and kiiberiad stories, where almost all the characters are robots that are far descendants of robots who escaped from people (people they are called palectuits and consider them mythical creatures).

Films

Starting almost from the 60s, together with the writing of fantastic stories and leads, films about artificial intelligence are removed. Many of the leads of the authors recognized all over the world are shielded and become a classic genre, others become a milestone in the development of film fantasics, such as a terminator and a matrix.

Notes

FAQ from John McCarthy, 2007
M. Andrew. Real life and artificial intelligence // "News of artificial intelligence", Rai, 2000
Gavrilova T. A. Khoroshevsky V. F. Knowledge Base Intellectual Systems: Textbook for universities
Averkin A. N., Gaaz-Rapoport M. G., Pospelov D. A. Explanatory dictionary of artificial intelligence. - M.: Radio and Communication, 1992. - 256 p.
G. S. Osipov. Artificial Intelligence: Study State and Looking To the Future
Ilyasov F. N. Mind is artificial and natural // Izvestia An Turkmen SSR, a series of social sciences. 1986. No. 6. P. 46-54.
Alan Turing, can the cars think?
Intellectual machines S. N. Korsakov
D. A. Pospelov. Changing computer science in Russia
To the history of cybernetics in the USSR. Essay first, sketch second
Jack Copeland. What Is Artificial Intelligence? 2000.
ALAN TURING, "Computing Machinery and Intelligence", Mind, Vol. LIX, NO. 236, October 1950, PP. 433-460.
Natural Processing:
Natural language processing applications include information search (including: Text Analysis and Machine Translation):
Gorban P. A. Neural trading knowledge from data and computer psychoanalysis
Machine training:
Alan Tyuring discussed how central theme Already in 1950, in his classic article Computing Machinery and Intelligence. ()
(PDF Scanned Copy of the Original) (Version Published in 1957, An Inductive Inference Machine, "Ire Convention Record, Section On Information Theory, Part 2, PP. 56-62)
Robotics:
pp. 916-932.
pp. 908-915
Blue Brain Project - Artificial Brain
Mild-Mannered Watson Skewers Human Opponents ON Jeopardy
20q.net Inc.
Axelrod R. The Structure of Decision: Cognitive Maps of Political Elites. - PrinceTon. University Press, 1976
John Stew. The mind of the brain is a computer program?
Penrose R. New king's mind. About computers, thinking and laws of physics. - m .: Urals, 2005. - ISBN 5-354-00993-6
AI as a global risk factor
... will behave eternal
http://www.rc.edu.ru/rc/s8/intellect/rc_intellect_zaharov_2009.pdf Orthodox view on the problem of artificial intelligence
Harry Harrison. Selection by Turing. - m .: Eksmo-press, 1999. - 480 p. - ISBN 5-04-002906-3.

Literature

The computer learns and argues (part 1) // The computer acquires a mind \u003d Artificial Intelligence Computer Images / Ed. V. L. Stefanyuk. - Moscow: Mir, 1990. - 240 s. - 100,000 copies. - ISBN 5-03-001277-X (Rus.); ISBN 705409155 (English)
Devyatkov V.V. Systems of artificial intelligence / ch. ed. I. B. Fedorov. - m.: Publishing house MSTU. N. E. Bauman, 2001. - 352 p. - (Informatics in Technical University). - 3000 copies. - ISBN 5-7038-1727-7

Korsakov S.N. Inscription a new way of research using machines comparing ideas / ed. A.S. Mikhailova. - M.: Mafi, 2009. - 44 s. - 200 copies. -

At the same time, there is also a point of view according to which intelligence can only be a biological phenomenon.

As indicated by the chairman of the St. Petersburg branch of the Russian Association of Artificial Intelligence T. A. Gavrilova, in English phrase aRTIFICIAL INTELLIGENCE It does not have the slightly fantastic anthropomorphic color, which it has acquired in a rather unsuccessful Russian translation. Word intelligence means "ability to reason intelligent", and not at all "intelligence" for which there is English analog intellect. .

Participants in the Russian Association of Artificial Intelligence give the following definitions of artificial intelligence:

Often, artificial intelligence is also called the simplest electronics to designate the presence of sensors and the automatic choice of operation mode. The word artificial in this case means that you should not expect from the skill system to find a new mode of operation in the situation not provided by the developers.

Artificial Intelligence Science Development Backgrounds

The history of artificial intelligence as a new scientific direction begins in the middle of the 20th century. By this time, many prerequisites for its origin have already been formed: the philosophers have long been disputes about the nature of the person and the process of knowledge of the world, neurophysiologists and psychologists have developed a number of theories regarding the work of the human brain and thinking, economists and mathematicians asked for optimal calculations and presentation of knowledge about the world in formalized form; Finally, the foundation of the mathematical theory of calculations was originated - the theory of algorithms - and the first computers were created.

The history of the development of artificial intelligence in the USSR and Russia

In 1964, the work of the Leningrad Logic of Sergei Maslov "The inverse method of establishing a classical predicate calculation of predicates was published, in which the method of automatic search for proof by theorems in the calculation of predicates was presented for the first time.

Until the 1970s, all studies have been conducted in the USSR in the framework of cybernetics. According to D. A. Pospelova, the science of "Informatics" and "Cybernetics" was mixed at this time, due to a number of academic disputes. Only in the late 1970s in the USSR begin to talk about the scientific direction "Artificial Intelligence" as a section of computer science. At the same time, the informatics itself was born, subdued to the PREDITER "Cybernetics". In the late 1970s, an explanatory dictionary of artificial intelligence is created, a three-year reference book on artificial intelligence and an encyclopedic dictionary on computer science, in which the sections "Cybernetics" and "artificial intelligence" are included along with other sections in computer science. The term "Informatics" in the 1980s is widespread, and the term "cybernetics" gradually disappears from the appeal, preserved only in the names of those institutions that arose in the era of the "cybernetic boom" of the late 1950s - early 1960s. Such a look at artificial intelligence, cybernetics and computer science is not divided by everyone. This is due to the fact that in the West borders of these sciences are somewhat different.

Approaches and directions

Approaches to understanding the problem

downward (eng. TOP-DOWN AI), semiotic - the creation of expert systems, knowledge bases and logical conclusions, imitating high-level mental processes: thinking, reasoning, speech, emotions, creativity, etc.;
ascending (eng. Bottom-Up AI), biological - study of neural networks and evolutionary calculations that simulate intelligent behavior based on biological elements, as well as the creation of appropriate computing systems, such as a neurocomputer or biocomputer.

The last approach, strictly speaking, does not apply to the science of AI in the sense of this John McCarthy, - they are united only by the general ultimate goal.

Turing Turing and an intuitive approach

The most general approach suggests that the AI \u200b\u200bwill be able to show behavior that does not differ from human, and in normal situations. This idea is a generalization of the Turing test approach, which claims that the car will be reasonable when it is able to maintain a conversation with an ordinary person, and he will not be able to understand what he speaks with the car (talking on correspondence).
Science fiction writers often offer another approach: AI will arise when the car will be able to feel and create. So, the owner Andrew Martina from the "Two-Year-Year Man" begins to treat him as a person when he creates a toy on his own project. And the diet from the star road, being able to communicate and learned, dreams of gaining emotions and intuition.

However, the last approach is unlikely to endure criticism with a more detailed consideration. For example, it is easy to create a mechanism that will evaluate some parameters of the external or internal environment and respond to their adverse values. We can say about such a system that it has feelings ("pain" - a reaction to the triggering of the impact sensor, "hunger" is a reaction to a low battery charge, etc.). And clusters created by Kohonen cards, and many other "intelligent" systems can be considered as a type of creativity.

Symbolic approach

Logic approach

A logical approach to creating artificial intelligence systems is aimed at creating expert systems with logical knowledge base models using predicate language.

Agent-oriented approach

Hybrid approach

Main article: Hybrid approach

Models and research methods

Symbolic modeling of mental processes

Main article: Modeling reasoning

Work with natural languages

An important direction is natural language processing In which the analysis of the possibilities of understanding, processing and generating texts on the "human" language is carried out. As part of this direction, the goal of such a natural language processing is set, which would be able to acquire knowledge independently, reading the existing text available on the Internet. Some direct applications of natural language processing include information search (including deep text analysis) and machine translation.

Presentation and use of knowledge

Machine learning

Robotics

Main article: Intellectual robotics

Machinerary creativity

Main article: Machinerary creativity

Other research areas

Modern artificial intellect

You can allocate two directions of development AI:

solving problems related to the approach to the specialized systems of the AI \u200b\u200bto human capabilities, and their integration, which is implemented by the nature of man ( see Intellect Strengthening);
the creation of an artificial mind representing the integration of already created II systems into a single system capable of solving the problems of humanity ( see strong and weak artificial intelligence).

But at the moment, in the field of artificial intelligence, there is an involvement of many subject areas, which are more practical attitude towards AI, and not fundamental. Many approaches were tested, but to the emergence of an artificial mind, no research group has yet come true. Below are only some of the most famous developments in the field of AI.

Application

Tournament Robocup.

Some of the most famous II systems:

Banks use artificial intelligence systems (SII) in insurance activities (actuarial mathematics), when playing the stock exchange and property management. Methods of recognition of images (including, both more complex and specialized and neural networks) are widely used in optical and acoustic recognition (including text and speech), medical diagnostics, spam filters, in air defense systems (definition of goals), as well as To ensure a number of other national security tasks.

Psychology and Cognitology

The methodology for cognitive modeling is intended for analysis and decision-making in poorly defined situations. Was proposed by Axelrod.

Philosophy

The term "strong artificial intelligence" introduced John Stewl, his own words approach and characterized:

Moreover, such a program will not be just a model of mind; She in the literal sense of the word herself will be mind, in the same sense in which the human mind is a mind.

On the contrary, supporters of weak AI prefer to consider programs only as a tool that allows you to solve certain tasks that do not require a complete spectrum of human cognitive abilities.

Ethics

Science fiction

In the work of science and philosophy, Stanislav Lema described and largely anticipated the creation of a virtual reality, artificial intelligence, nanorobots and many other problems of artificial intelligence philosophy. It is especially worth noting the futurology of the amount of technology. In addition, in the adventures of Iyon, the relationships of living beings and cars are repeatedly described: the riot of the onboard computer with subsequent unexpected events (11 travel), the adaptation of robots in human society ("washing tragedy" from "Memonies of Pichery"), building an absolute order on the planet By processing living inhabitants (24th journey), the inventions of the crocoon and the diagnostics ("Memories of the Iyon of Pacific"), a psychiatric clinic for robots ("Memories of the Sail"). In addition, there is a whole cycle of the ages and kiiberiad stories, where almost all the characters are robots that are far descendants of robots who escaped from people (people they are called palectuits and consider them mythical creatures).

Films

Notes

FAQ from John McCarthy, 2007
M. Andrew. Real life and artificial intelligence // "News of artificial intelligence", Rai, 2000
Gavrilova T. A. Khoroshevsky V. F. Knowledge Base Intellectual Systems: Textbook for universities
Averkin A. N., Gaaz-Rapoport M. G., Pospelov D. A. Explanatory dictionary of artificial intelligence. - M.: Radio and Communication, 1992. - 256 p.
G. S. Osipov. Artificial Intelligence: Study State and Looking To the Future
Ilyasov F. N. Mind is artificial and natural // Izvestia An Turkmen SSR, a series of social sciences. 1986. No. 6. P. 46-54.
Alan Turing, can the cars think?
Intellectual machines S. N. Korsakov
D. A. Pospelov. Changing computer science in Russia
To the history of cybernetics in the USSR. Essay first, sketch second
Jack Copeland. What Is Artificial Intelligence? 2000.
ALAN TURING, "Computing Machinery and Intelligence", Mind, Vol. LIX, NO. 236, October 1950, PP. 433-460.
Natural Processing:
Natural language processing applications include information search (including: Text Analysis and Machine Translation):
Gorban P. A. Neural trading knowledge from data and computer psychoanalysis
Machine training:
Alan Turing discussed as a central topic already in 1950, in its classical article Computing Machinery and Intelligence. ()
(PDF Scanned Copy of the Original) (Version Published in 1957, An Inductive Inference Machine, "Ire Convention Record, Section On Information Theory, Part 2, PP. 56-62)
Robotics:
pp. 916-932.
pp. 908-915
Blue Brain Project - Artificial Brain
Mild-Mannered Watson Skewers Human Opponents ON Jeopardy
20q.net Inc.
Axelrod R. The Structure of Decision: Cognitive Maps of Political Elites. - PrinceTon. University Press, 1976
John Stew. The mind of the brain is a computer program?
Penrose R. New king's mind. About computers, thinking and laws of physics. - m .: Urals, 2005. - ISBN 5-354-00993-6
AI as a global risk factor
... will behave eternal
http://www.rc.edu.ru/rc/s8/intellect/rc_intellect_zaharov_2009.pdf Orthodox view on the problem of artificial intelligence
Harry Harrison. Selection by Turing. - m .: Eksmo-press, 1999. - 480 p. - ISBN 5-04-002906-3.

Literature

The computer learns and argues (part 1) // The computer acquires a mind \u003d Artificial Intelligence Computer Images / Ed. V. L. Stefanyuk. - Moscow: Mir, 1990. - 240 s. - 100,000 copies. - ISBN 5-03-001277-X (Rus.); ISBN 705409155 (English)
Devyatkov V.V. Systems of artificial intelligence / ch. ed. I. B. Fedorov. - m.: Publishing house MSTU. N. E. Bauman, 2001. - 352 p. - (Informatics in Technical University). - 3000 copies. - ISBN 5-7038-1727-7

Korsakov S.N. Inscription a new way of research using machines comparing ideas / ed. A.S. Mikhailova. - M.: Mafi, 2009. - 44 s. - 200 copies. -

Artificial intelligence is an area of \u200b\u200bscience engaged in modeling the intellectual activity of a person. Around more than 700 years ago in medieval Spain, artificial intelligence took shape into an independent scientific region in the middle of the XX century.

Methods of artificial intelligence made it possible to create effective computer programs in a wide variety of previously considered unavailable for formalization and algorithmization, spheres of human activity, such as medicine, biology, zoology, sociology, cultural studies, political science, economics, business, criminalistics, etc. The ideas of training and self-learning computer programs, knowledge accumulation, fuzzy and non-specific knowledge of the processing of processing and non-specific knowledge allowed to create programs creating wonders. Computers are successfully fighting for the title of world chess champion, model creative human activity, creating musical and poetic works, recognize images and scenes, recognize, understand and proceed, texts on a natural human language. Necrocomputers, created in the image and similarity of the human brain, successfully cope with the management of complex technical objects, diagnosis of human diseases, faults of complex technical devices; Weather predicted and currencies, voting results; detect hackers and potential banks; Help the applicants to choose the right specialty, etc.

We are already accustomed to the fact that computers will "smart" literally in front of the eyes, and computer programs are becoming more and more intellectual. In itself, the concept of intelligence constantly undergoes changes as the science and man develops. It has long been not considered intellectual tasks consisting in performing arithmetic operations of addition, multiplication, division. The intellectual task of integrating the differential equation is not considered if it is known for it strictly deterministic algorithm. Currently, it is customary to be intellectual tasks that modern stage Algorithmization is not amenable to the traditional sense of the word. These are tasks to solve the manipulation with fuzzy, non-specific, unreliable, vague and even unconventional knowledge.

Let's start considering the provisions of AI with terms and definitions.

Term intelligence (Intelligence) comes from Latin Intellectus - which means mind, reason, mind; Thinking abilities of man. Respectively artificial Intelligence (ARTIFICIAL Intelligence) - AI (AI) is usually interpreted as the property of automatic systems to take on individual functions of human intelligence, for example, choose and make optimal solutions based on previously obtained experience and rational analysis of external influences.

The concept of "intelligence" is used today both in the technique, and in technical disciplines, which differs from the definitions formed in the context of psychological and philosophical research of consciousness. Under intellect We will understand the ability of thinking to foresee events, foresee the results of our own actions, analyze and evaluate their condition and the environment and make decisions by consulting with their ideas about the world around. Definition given by Academician N.N. Moiseev, considers intellectual activities from the standpoint of computer science. But it allocates the most important thing in intelligence is the ability to be distracted thinking, abstraction, due to which self-consciousness and reflection arise.

So, intelligence - This is the ability of the brain to solve (intelligent) tasks by acquiring, memorizing and targeted knowledge transformation in the learning process on experience and adaptation to a variety of circumstances.

At the same time, the term "knowledge" means not only the information that enters the brain through the senses. This type of knowledge is extremely important, but insufficient for intellectual activity. The fact is that objects of the environment of us have a property not only to influence organs of feelings, but also to be with each other in certain relationships. It is clear that in order to implement intellectual activity (or at least to exist), you must have a model of this world in the knowledge system. In this information model of the environment, real objects, their properties and relations between them are not only displayed and remembered, but also, as noted in this definition of intelligence, may mentally "purposefully convert." At the same time, it is essential that the formation of the external environment model occurs "in the process of learning on experience and adaptation to a variety of circumstances."

Intellectual task. In order to clarify what the intellectual task is distinguished from simply tasks, it is necessary to introduce the term "algorithm" - one of the cornerstone of cybernetics.

Under algorithmunderstand the exact prescription of the execution of operations in a certain order to solve any problem from some given class (sets) tasks. The term "algorithm" occurs on behalf of Uzbek mathematics by Al-Khorezmi, which in the 9th century proposed the simplest arithmetic algorithms. In mathematics and cybernetics, the class of tasks of a particular type is considered solved when an algorithm is installed for solving it. Finding algorithms is a natural purpose of a person when solving a variety of tasks classes. Saying an algorithm for problems of some given type is associated with thin and complex arguments requiring great ingenuity and high qualifications. Tasks associated with finding the algorithm for solving the class of tasks of a certain type will be called intellectual.

As for the tasks, the solutions algorithms are already established, as noted by a well-known specialist in the field of II M. Minsk, "it is unnecessary to attribute such a mystical properties as" intellectuality ". In fact, after such an algorithm has already been found, the process of solving the corresponding tasks becomes such that it may accurately perform a person, a computing machine (properly programmed) or a robot that does not have the slightest idea of \u200b\u200bthe essence of the task itself. It is only required that a person who decisive task can be able to perform the elementary operations that the process is developing, and, in addition, so that it is pedantically and neatly guided by the proposed algorithm. Such a person acting as they say in such cases is clean automatically, it can successfully solve any task of the considered type.

Therefore, it seems to be completely natural to exclude their class of intelligent such tasks for which standard solution methods exist. Examples of such tasks include purely computational problems: the solution of a system of linear algebraic equations, numerical integration of differential equations, etc. To solve this kind of tasks, there are standard algorithms that are a certain sequence of elementary operations that can be easily implemented as a program for computing cars. In contrast, for a wide class of intellectual tasks, such as image recognition, game of chess, proof of theorems, etc., opposite this formal partitioning of the decision to find a solution to individual elementary steps is often very difficult, even if their decision is easy.

Thus, it is possible to rephrase the definition of intelligence as a universal superlong, which is capable of creating algorithms for solving specific tasks.

Another interesting comment here is that the profession of a programmer, based on our definitions, is one of the most intellectual, since the product of the programmer's activities are programs - algorithms in its pure form. That is why the creation of even the elements of the AI \u200b\u200bshould greatly increase the productivity of his labor.

Brain activity (possessing intelligence), aimed at solving intellectual tasks, will be called thinking, or intellectual activity. Intellect and thinking are organically associated with solving such tasks as proof theorems, logical analysis, recognition of situations, behavior planning, game and management in uncertainty. Characteristic features of intelligence manifested in the process of solving problems are the ability to learn, generalize, accumulate experience (knowledge and skills) and adapting to changing conditions in the process of solving problems. Thanks to these qualities of intelligence, the brain can solve a variety of tasks, and also easily rebuild with solving one task to another. Thus, the brain endowed with intelligence is a universal means of solving a wide range of tasks (including informalized) for which there are no standard, pre-known solutions methods.

It should be borne in mind that there are other, pure behavioral (functional) definitions. So, according to A. N. Kolmogorov, any material systemWith which you can discuss the problems of science, literature and art, it has intelligence. Another example of the behavioral interpretation of the intellect may be the known definition of A. Turing. His meaning is as follows. IN different rooms There are people and a car. They cannot see each other, but have the ability to exchange information (for example, using email). If in the process of dialogue between the participants of the game, people cannot be installed that one of the participants is a car, then such a car can be considered a possessing intelligence.

By the way, a plan for imitation of thinking proposed by A. Turing was interesting. "Trying to imitate the intelligence of an adult, - writes Turing," we have to think a lot about the process, as a result of which the human brain has reached its present state ... Why, instead of trying to create a program that imitating an adult intelligence, do not try to create a program. which would imitate the child's intellect? After all, if the child's intelligence receives appropriate education, it becomes an adult intelligence ... Our calculation is that the device, it can be easily programmed ... Thus, we dismember our problem into two parts: on the task of building a "child program" and the task of "upbringing" of this program. "

Run ahead, we can say that it is this way that almost all II systems use. After all, it is clear that it is almost impossible to lay all the knowledge of a rather complicated system. In addition, only on this path will be shown above the signs of intellectual activity (accumulation of experience, adaptation, etc.).

The term "artificial intelligence" was introduced in 1956 in 1956 by Professor of the Massachusetts Institute of Technology, J.Makarti at the meeting of American specialists in the field of science related to theory and practice of the study of computing processes. At this meeting in Dortmut College, which Americans consider the first conference on AI, two main tasks in the new scientific and technical industry were formulated: reveal the mechanism of human thinking and build an electronic machine that could imitate this process.

A single definition that fully describes this scientific region does not exist to this day. Among many points of view, three are dominated today. According to the first - research in the field of AI is fundamental studies, within which models are developed and methods for solving problems, traditionally considered intellectual and non-previous formalization and automation. According to the second point of view, the new direction is associated with the new ideas of solving the tasks on a computer, with the development of fundamentally different programming technology, with the transition to an architecture of a computer that rejects the classical architecture, which goes back to the first computer. Finally, the third point of view, apparently, the most pragmatic is that as a result of work in the field of artificial intelligence, many applied systems are born that decisive problems for which previously created systems were unsuitable.

Of course, all these three points of view are mutually related, fundamental studies are developing in the field of II, a new programming technology, a new technical equipment architecture, and all this is used to create applied systems designed to work in a wide variety of areas.

Under artificial intelligence We will understand the field of scientific research, within which models are being developed, methods, technical and software solutions to tasks, traditionally considered intellectual and formalization and automation.

Under intellectual systems Any biological, artificial or formal systems that show the ability to target behavior are understood. The latter includes properties (manifestations) of communication, accumulation of knowledge, decision-making, learning, adaptation, etc.

Systems II Called systems intended to perform such practical tasks on the computer, which are called intelligent if they are performed by people. In the theory of AI often, the AI \u200b\u200bsystems are called intellectual systems.

Another definition of the concept of "intellectual system" in the AI \u200b\u200bproposed by Pospelovyov D.A. The system is considered intellectual if the following three basic functions are implemented in it:

1) Presentation and processing function. The intelligent system should be able to accumulate knowledge about the world around the world, classify and evaluate them from the point of view of pragmatics and consistency, initiate the processes of obtaining new knowledge, relate new knowledge with knowledge stored in the knowledge base.

2) Correspondence function. The intelligent system should be able to form new knowledge using the logical conclusion and mechanisms for identifying patterns in accumulated knowledge, receive generalized knowledge based on private knowledge and logically plan their activities.

3) Communication feature. The intelligent system should be able to communicate with a language in a language close to natural (HEA) and receive information through channels similar to those that the person uses when the surrounding world is perceived, first of all, visual and sound, be able to form "for themselves" or at the request of a person Explanations of our own activities, assist a person at the expense of knowledge that is stored in its memory, and the logical means of reasoning.

Artificial intelligence can be defined as a scientific discipline that is engaged in modeling reasonable behavior. This definition has one significant drawback - the concept of intelligence is difficult to explain. Most people are confident that they will be able to distinguish "reasonable behavior" when it will face. However, it is unlikely that anyone can give an intelligence definition, quite concrete to assess the presumably sensible computer program and at the same time reflecting the viability and complexity of the human mind.

So, the problem of determining the artificial intelligence comes down to the problem of definition of intelligence at all: is it of something united, or is this term combines a set of scattered abilities? To what extent intelligence can be created? What is creativity? What is intuition? Is it possible to judge the presence of intelligence only by observed behavior? How are knowledge in the nervous tissues of living beings, and how can I apply in the design of intelligent devices? Is it possible to achieve rationality in general through computer technology, or the essence of intelligence requires the wealth of feelings and experience inherent in only biological beings?

No response has not yet been found for these issues, but they all helped to form tasks and a methodology that make up the basis of modern artificial intelligence. Partly the attractiveness of artificial intelligence in the fact that it is the original and powerful weapon to study these problems. Artificial intelligence provides a means and test model for intelligence theories: these theories can be formulated in the language of computer programs, and then tested.

For these reasons, the definition of artificial intelligence, given at the beginning of the article, does not give an unambiguous characteristic for this area of \u200b\u200bscience. It only puts new questions and opens the paradoxes in the area, one of the main tasks of which is to search for self-determination. However, the search problem accurate definition Artificial intelligence is quite explained. The study of artificial intelligence is another discipline, and its structure, the range of issues and techniques are not as clearly defined, as in more mature sciences, such as physics.

Artificial intelligence is designed to expand the capabilities of computer sciences, and not to determine their borders. One of the important tasks facing researchers is to maintain these efforts with clear theoretical principles.

Any science, including artificial intelligence, considers some circle of problems and develops approaches to solving them. The history of artificial intelligence, stories about personalities and their hypothesis, which are based on this science may be able to explain why some problems have become dominated in this area and why the methods used today were taken to solve them.

Creating intelligent machines, especially intelligent computer programs ; 2) Property of intelligent systems perform creative functions, which are traditionally considered the prerogative of a person. Large: -1

AI is associated with a similar task of using computers to understand human intelligence, but it is not necessarily limited to biologically believable methods. Large: -1

The origin and understanding of the term "artificial intelligence"

The definition of artificial intelligence, given in the preamble, given by John McCarthy in 1956 at a conference in the University of Dartmouth, is not connected directly with the understanding of the intellect in humans. According to McCarthy, liberators are free to use methods that are not observed in humans, if necessary for solving specific problems .

Participants in the Russian Association of Artificial Intelligence give the following definitions of artificial intelligence:

The scientific direction within which the tasks of the hardware or software modeling of those types of human activity are put up and solved, which are traditionally considered intellectual Averkin A. N., Gaaz-Rapoport M. G., Pospelov D. A. Explanatory dictionary of artificial intelligence. - M.: Radio and Communication, 1992. - 256 p..
Property of intelligent systems perform functions (creative), which are traditionally considered a prerogative of a person. At the same time, the intelligent system is a technical or software system that can solve the tasks traditionally considered creative, belonging to a particular subject area, knowledge of which is stored in the memory of such a system. Structure intellectual System Includes three main blocks - knowledge base, solver and intelligent interface, allowing you to communicate with computer without special programs For data entry .
Science entitled "Artificial Intellect" is included in the complex of computer sciences, and technology-based technology to information technology. The task of this science is to recreate with the help of computing systems and other artificial devices of reasonable reasoning and actions G. S. Osipov. Artificial Intelligence: Study State and Looking To the Future.

One of the private definitions of intelligence, common to humans and "machines", can be formulated as follows: "Intellect - the ability of the system to create during the self-study of the program (first of all heuristic) to solve the tasks of a certain class of complexity and solve these tasks" Ilyasov F. N. Mind is artificial and natural // Izvestia An Turkmen SSR, a series of social sciences. 1986. No. 6. P. 46-54..

Artificial Intelligence Science Development Backgrounds

The history of the development of artificial intelligence in the USSR and Russia

In the USSR, work in the field of artificial intelligence began in the 1960s . The Moscow University and Academy of Sciences carried out a number of pioneer studies, headed by Veniamin Pushkin and D. A. Pospelov. From the beginning of the 1960s M. L. Zetlin with colleagues developed issues related to the training of finite automata.

Until the 1970s, all studies have been conducted in the USSR in the framework of cybernetics. According to D. A. Pospelova, the science of "Informatics" and "Cybernetics" was mixed at this time, due to a number of academic disputes. Only in the late 1970s in the USSR begin to talk about the scientific direction "Artificial Intelligence" as a section of computer science. At the same time, the informatics itself was born, subdued to the PREDITER "Cybernetics". In the late 1970s, an explanatory dictionary of artificial intelligence is created, a three-year reference book on artificial intelligence and an encyclopedic dictionary on computer science, in which the sections "Cybernetics" and "artificial intelligence" are included along with other sections in computer science. The term "Informatics" in the 1980s is widely distributed, and the term "cybernetics" gradually disappears from the appeal, preserving only in the names of those institutions that arose in the era of the "cybernetic boom" of the late 1950s - early 1960s D. A. Pospelov. Formation of computer science in Russia. Such a look at artificial intelligence, cybernetics and computer science is not divided by everyone. This is due to the fact that in the west border of the data of sciences are somewhat different

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What is artificial intelligence? History of development and prospects. The main directions of research

Artificial Intelligence Science Development Backgrounds

The history of the development of artificial intelligence in the USSR and Russia

Approaches and directions

Approaches to understanding the problem

Turing Turing and an intuitive approach

Symbolic approach

Logic approach

Agent-oriented approach

Hybrid approach

Models and research methods

Symbolic modeling of mental processes

Work with natural languages

Presentation and use of knowledge

Machine learning

Robotics

Machinerary creativity

Other research areas

Modern artificial intellect

Application

Psychology and Cognitology

Philosophy

Ethics

Science fiction

Films

see also

Notes

Literature

Artificial Intelligence Science Development Backgrounds

The history of the development of artificial intelligence in the USSR and Russia

Approaches and directions

Approaches to understanding the problem

Turing Turing and an intuitive approach

Symbolic approach

Logic approach

Agent-oriented approach

Hybrid approach

Models and research methods

Symbolic modeling of mental processes

Work with natural languages

Presentation and use of knowledge

Machine learning

Robotics

Machinerary creativity

Other research areas

Modern artificial intellect

Application

Psychology and Cognitology

Philosophy

Ethics

Science fiction

Films

see also

Notes

Literature

The origin and understanding of the term "artificial intelligence"

Artificial Intelligence Science Development Backgrounds

The history of the development of artificial intelligence in the USSR and Russia

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