Artificial intelligence beat a person in games (Go, Chess and others). Towards Deep Blue: A Step-by-Step Guide to Building a Simple AI for Playing Chess Chess and AI Learning Project

Developed by engineers at the Massachusetts Institute of Technology. Fischer checkmated the computer three times and won by a landslide. In his letters, the chess player wrote that programs make "blunders", and called the computers themselves "useless pieces of iron."

But in the same year, Monty Newborn, one of the first scientists to study computer chess, said prophetic words:

“Grandmasters used to come to computer chess tournaments to have a laugh. Now they come to observe, and in the future they will study there.”

Bobby Fischer after defeating the computer. Photo: Getty Images

It seems that people have some kind of innate love for mind games. When King Charles I of England was sentenced to death in 1649, he took two things with him to his execution - a bible and a set of chess. The famous artist of the 20th century, Marcel Duchamp, at the peak of his career, suddenly left for Argentina and began carving chess pieces from wood, and in general became interested in chess. In the 19th century, a mysterious story related to the game of Go occurred in Japan. According to legend, the spirits prompted one famous player three brilliant moves. As a result, he was able to win, and his opponent after the game fell to the floor, choked with blood and died.

Computers are far from all this mysticism, but in just a couple of decades they have studied mind games more deeply than humanity has in millennia. In 2014, the company acquired DeepMind for $400 million to "carry out the most unusual and complex research, the ultimate goal of which is to unravel the essence of intelligence." In particular, scientists wanted to teach a computer to play Go. This game is much more difficult than chess. In 1985, a Taiwanese industrial magnate said he would pay $1.4 million for a program that could beat the best Go player. In 1997, the magnate died, and three years later his offer expired - no one was able to take the prize.

Now it could belong to the DeepMind AlphaGo program, which uses modern neural networks. A year ago, she was international go champion Lee Sedol. In May of this year, she again defeated the best Go player, as well as a team of five other professional players.

AlphaGo has become the absolute champion. But soon after her high-profile victories, oblivion awaits her. At the end of May, DeepMind quietly announced that AlphaGo was leaving the competitive scene. To mark the occasion, the company published 50 variations of the games that the program played against itself. In the future, DeepMind wants to release a final research paper that will describe the effectiveness of the program's algorithm.

As for chess, mankind lost the palm in them 20 years before these events, when chess player Garry Kasparov lost to the IBM Deep Blue supercomputer. Chess and Go are not the only games AI is trying to teach. They tried to teach the computer checkers, short backgammon, reversi, poker and many other board games. And human intelligence can no longer be compared with artificial intelligence. This is partly due to advances in technology. For example, back in 1997, the Deep Blue computer ranked 259th in the list of the fastest supercomputers in the world and could perform about 11 billion operations per second. Now, thanks to modern algorithms, even your smartphone is able to defeat Kasparov.

Garry Kasparov vs Deep Blue computer. On the left is one of the IBM engineers, Xiong Feixiong. Photo: Getty Images

Such achievements of AI have caused quite human emotions in people: sadness, depression and despair. After Lee Sedol was defeated by AlphaGo, he went through an existential crisis. “I questioned human ingenuity,” he admitted after the match. “I wondered if all the moves in Go that I knew were correct.” According to one eyewitness, after the defeat, Lee looked like he was "physically ill." Kasparov felt no better after losing to the computer. When he returned to the hotel, he simply undressed, got into bed and stared at the ceiling.

"The computer analyzes some positions so deeply that it plays like a god," Kasparov said.

Deep Blue showed the public for the first time that a computer can outperform humans in solving intellectual problems. “Then it was a shock,” said Murray Campbell, co-founder of Deep Blue. “Now we are gradually getting used to this idea.” However, it is not clear what awaits humanity in the future. How can achievements be used in the real world in games? Campbell's answer to this question sounds pessimistic. "It's hard to find a good example of such success in board games," he said. - In the early 90's, an IBM employee named Gerald Tesauro tried to teach AI to play backgammon and made some advances in stimulated learning. Now his methods are often used in robotics. However, his case is rather an exception to the rule.

Grishanin E.A. Durin S.V. Contents 1. What is artificial intelligence? 2. About knowledge bases. 3. Test tasks. Artificial intelligence. In the 60s of the XX century, a new branch of computer science appeared, which was called "Artificial Intelligence". The encyclopedic dictionary says: "Intellect (from Latin intellectus - knowledge, understanding, reason) - the ability to think, rational knowledge." To the fullest extent, this ability is peculiar only to people. The subject of study of the science "Artificial Intelligence" is human thinking. Scientists are looking for an answer to the question: how does a person think? The goal of these studies is to create a model of human intelligence and implement it on a computer. Somewhat simplified, the above goal sounds like this: - To teach the machine to think. Starting to solve a problem, a person often does not have a clear program of action. He builds this program himself in the course of work. For example, when playing chess, a chess player knows the rules of the game and has the goal of winning the game. His actions are not pre-programmed. They depend on the actions of the opponent, on the emerging position on the board, on the wit and personal experience of the chess player. There are many other human activities that cannot be programmed in advance. For example, composing music and poetry, proving a theorem, literary translation from a foreign language, diagnosing and treating diseases, and much more. You are well aware that any work the computer performs according to the program. Programs are written by people, and the computer formally executes them. The developers of artificial intelligence systems are just trying to teach a machine, like a person, to independently build a program of its actions, based on the condition of the problem. You can also say this: the goal is to turn the computer from a formal executor into an intellectual executor. Formal executor data program Execution of the program results Intelligent executor data Construction of the program Execution of the program results Model of functioning of formal and intellectual executor Any artificial intelligence system operates within a specific subject area (medical diagnostics, legislation, mathematics, economics, etc.). Like a specialist, a computer must have knowledge in this area. Knowledge in a specific subject area, formalized in a certain way and embedded in the memory of a computer, is called a computer knowledge base. For example, you want to use a computer to solve problems in geometry. If there are 500 tasks of different content in the problem book, then with the traditional use of a computer, 500 programs will have to be written. If an artificial intelligence specialist takes up this problem, then he will approach it in a completely different way. He will put the knowledge of geometry into the computer (as the teacher's knowledge is laid in you). Based on this knowledge and with the help of a special algorithm of logical reasoning, the computer will solve any of the 500 problems. To do this, it will be enough to tell him only the condition of the problem. Artificial intelligence systems operate on the basis of the knowledge bases embedded in them. Every student knows that in order to solve any problem, it is not enough to remember the rules, laws, formulas, but you still need to be able to think, reason, and apply this knowledge. Human thinking is based on two components: a stock of knowledge and the ability to reason logically. Hence, two main tasks follow when creating intelligent systems on a computer: - knowledge modeling (development of knowledge formalization methods for entering them into computer memory as a knowledge base); - modeling of reasoning (creation of computer programs that imitate the logic of human thinking in solving various problems). Expert systems are one of the types of artificial intelligence systems. Usually the word "expert" refers to a person with great knowledge and experience in a particular area. Knowledge of this level is embedded in computer expert systems. The purpose of expert systems is to consult the user, help in making decisions. Such assistance becomes especially important in extreme situations, for example, in conditions of a technical accident, an emergency operation, while driving. The computer is not subject to stress. He will quickly find the optimal, safe solution and offer it to the person. However, the final decision is made by the individual. Briefly about the main Artificial intelligence (AI) is a branch of computer science. The subject of AI is human thinking; the goal is to create intelligent systems on a computer. Examples of areas in which artificial intelligence systems are being created: chess and other games, writing poetry and music, translating texts from one language to another, robotics, forensics (fingerprint identification, etc.), medical diagnostics. Artificial intelligence systems work on the basis of the knowledge embedded in them in a certain area. The knowledge model embedded in the memory of a computer is called a computer knowledge base. Human thinking is based on two components: the stock of knowledge and the ability to reason logically. AI systems implement a reasoning model (human logic). Based on the knowledge base and the reasoning model, the AI ​​system itself programs its work when solving any problem. An expert system is an AI system that contains the knowledge and experience of an expert in a given subject area. Here is the composition of the knowledge base "Relatives": Facts: Leo is Andrey's father; Leo is Peter's father; Andrei - Alexei's father; Peter is Michael's father; Peter is Dmitry's father. Rules: every man is the son of his father; grandfather - father's father; brothers are sons of the same father; uncle - father's brother; nephew - brother's son; grandson is the son of a son. Based on these facts and rules, it is possible, by logical reasoning, to establish all kinds of family ties between the men of this family. Pay attention to two features of the knowledge base: - the facts are private, and the rules are general (fair for any family); - only basic facts are included in the knowledge base. Indeed, it is enough to know who is the father of whom in order to use the rules to determine other family ties. On the basis of such a knowledge base, it is possible to build an expert system in the field of kinship between men. To use it in relation to another family, it is enough to change the list of facts, and the rules, of course, will remain the same. Comparing the database with the knowledge base, we come to the conclusion: the database contains only facts, the knowledge base contains facts and rules. Home About knowledge bases. You are already familiar with the concept of "database". A database (DB) is an information model of some real system in computer memory. It was said above that the knowledge base (KB) is a model of human knowledge in a particular subject area. Let's show the difference between a database and a knowledge base using a specific example. Consider this issue on the example of family ties between men of the same family. Here is how they look in the graphical form of a family tree: Leo Petr Andrey Mikhail Dmitry Alexey Family tree Here the lines represent the relationship between a father (at the top level) and a son (at the bottom level). Family ties Male Leo Sons Father Grandfather Brothers Uncles Nephews Don't know Don't know Grandchildren Andrey, Peter Don't know Don't know Don't know Andrey Alexey Lev Don't know Peter Don't know Mikhail Dmitry no Peter Mikhail, Dmitry Lev Don't know Andrey Don't know Alexey no Alexey No Andrey Lev no no Mikhail No Peter Lev Dmitry Andrey no no Dmitry No Peter Lev Mikhail no no no Peter Andrey Alexey Mikhail Dmitry In Table 9.1, information about family ties between the same men is presented in expanded form. Using a relational DBMS, it is easy to create a relational database based on this table. Turning to her with requests, you can determine who is the father, grandfather, brother of whom. This table is an information model of the "family" object. Now let's move on to building the knowledge base. The subject area here is family ties between men of the same family. There are various types of knowledge models in artificial intelligence. We will consider only one of them, which is called the logical knowledge model. This approach is used in the PROLOG programming system (Prolog is discussed in the second part of the book). According to the logical model, the knowledge base consists of facts and rules. And now let's give a general definition of the concepts of "fact" and "rule". A fact is a message (information) about a specific event, about a property of a specific object, about its connection with other objects. For example, the following statements are facts: - pine - coniferous tree; - Columbus discovered America in 1492; - the density of water is 1 g/cm; - King Solomon - son of King David; - Leo Tolstoy is a Russian writer. A rule is a statement that has more generality than a fact. Rules define some concepts through others, establish the relationship between various properties of objects, formulate the laws of nature or society. The knowledge base is a collection of fundamental facts and rules in a particular subject area. Recently, a new specialty “knowledge engineer” has appeared, whose task is to formalize knowledge, develop knowledge bases and create artificial intelligence systems based on them. Our example is very simple. Here it is not difficult to guess what facts are fundamental, and to formulate a complete set of rules. In more complex subject areas, this task is much more difficult. Often only a major specialist (expert) or a team of specialists with great knowledge in this field can solve it. Briefly about the main thing. The logical model of knowledge in a particular subject area is represented by a knowledge base composed of facts and rules. A fact is information about a specific event, about a property of a specific object, about its connection with other objects. Rules define some concepts through others, establish the relationship between various properties of objects, formulate the laws of nature or society. The knowledge base includes "only the fundamental facts for this subject area. Home Test tasks 1. 2. 3. 4. Task No. 1 Task No. 2 Task No. 3 Task No. 4 End When did the direction called "Artificial Intelligence" appear in computer science? A. In the 50s B. In the 60s C. In the 70s D. In the 80s Right Next Think Next What is a knowledge base? A. The knowledge base is information about a specific event, about the property of a specific object, about its connection with other objects. B. A knowledge base is a set of fundamental facts and rules in a particular subject area C. A knowledge base is D. A knowledge base is a development statement that has more generality than a fact. knowledge formalization methods for entering them into computer memory as a knowledge base What is reasoning modeling? A. Creation of computer programs, B. Development of methods that imitate the logic of human thinking in solving various problems. formalization of knowledge to enter them into computer soldering as a knowledge base. C. This is a model of human knowledge in D. This is an algorithm for a specific subject area. recorded in the language of the performer. What is a FACT? A. Any object consisting of B. This information about the composition and C. A message about a specific D. This is a certain order of many interconnected parts and the structure of the system, presented in a graphic existing as a whole. form. event and property of a particular object, its relationship with other objects. combining the elements that make up the system.

The history of the development of automation and computer technology is strangely connected with chess. In the XVIII century. "thinking" chess automata were used for tricks and hoaxes. The first apparatus with real artificial intelligence, created in Spain at the beginning of the 20th century, was able to checkmate a chess player with a king and a rook. Apparently, it is no coincidence that one of the first truly intelligent tasks assigned to programmers at the dawn of computing was the game of chess. One of those who created the first chess programs, Doctor of Technical Sciences, Professor Vladimir Lvovich Arlazarov, talks about chess programs and the connection of this ancient game with the development of artificial intelligence technologies.

- When it was found out that computers can not only calculate, as it was invented from the very beginning, that behind arithmetic operations there is a logical operation that not only performs auxiliary functions in the activities of computing programs, but also with the help of which it is possible to solve independent problems, it became clear: it is worth trying to put intellectual tasks on the computer. Somewhere from the end of the 40s to the end of the 50s, this was actively discussed, moreover, semi-philosophical questions were posed: maybe computers will be smarter than people? And then what? And all in all seriousness. Now such questions are not raised, after all, 40 years have passed. Then, at the dawn of computing, we only realized what machines could do in principle. We realized that the human brain is a device similar to a computer, and a thousand, a million times more powerful, but it is fundamentally a little different. It became clear that at least most of the rational problems that a person solves can be put before a machine. Therefore, you can try to write programs that solve these problems. One, two, a thousand ... after all, a person also solves not an infinite number of problems. And it is possible, so to speak, to program all the intellectual activity of a person.

– And why did you decide to turn to the game?

“As I said, there has been a lot of discussion about whether a machine can think. However, it is quite clear that if we are talking about programmers, about people who do not deal with philosophy, but with a real computer, then the question is not whether a machine can fundamentally do something, but in the search for examples of where machines decide intellectual tasks, and those that are accessible to a person in his intellectual activity. The line here, of course, is not clear. But it is clear that if a person multiplies 20-digit numbers, then he does not deal with a deeply intellectual task, since it is very easy to find a trivial algorithm for its implementation, which is known to every schoolchild. But those tasks where it is absolutely clear that a person does not have any a priori algorithm, but he nevertheless solves them well, we will call intellectual. The first contenders for the role of such tasks are games, for the simple reason that at least the rules are clearly formulated. The task is extremely difficult, and the rules of the game are easy to formulate, and thus it is easy to determine the functions of the machine. On the other hand, chess is a difficult task for a person, which somehow has never been discussed and is not being discussed now.

- And why did you choose chess from the games? Maybe a tradition?

Why only chess? We also tried cross movies and other games. But chess has many advantages over other games. If in simple games a machine beats a person, then this does not surprise anyone. Chess is a difficult game, and the victory of the computer is significant here. Then in chess, unlike a number of other games, there are many differentiable quality criteria, that is, one can determine: the machine plays well, the machine plays better, better, better. In many other games, such gradations are very difficult to establish. In some of them, the machine is either taught to play absolutely accurately, and thus all interest in the game is immediately lost, or it plays very badly. And in chess, not abstract, but, so to speak, mastered, there are so many levels that with their help it is possible to determine the class of the machine's game.

– So, it is clear why chess was one of the first and most important tasks of artificial intelligence. What methods were used to solve it?

– From the very beginning, the technique of solving the problem of a chess game was gradually mastered. In principle, chess is a finite game, and with mathematical rigor it can be proved that in any position there is an abstract best move for each of the opponents, and hence some result. Therefore, it is necessary to describe an algorithm in which this game can be calculated to the end. The only disadvantage of this algorithm is that it takes a long time. And we have not come close to those orders of time that are needed to calculate, say, chess to the end from the initial position. Over the past fifty years, the task in terms of time has remained infinitely complex. Well, infinity minus ten is still infinity. But if you need time, say, 10 to the 100th power of years, and you speed up the car, say, 100 times, and get 10 to the 98th power of years, then this is unlikely to make you feel better. Therefore, the main algorithm is exhaustive, trivial: if I go this way, then the enemy has so many possibilities. The options grow exponentially and form chains. But the number of positions is generally finite, and there are not so many of them on each chain. Chains are combined into trees, which again are not infinite. True, they grow exponentially, and the number of chains increases. So, an important question arises: do we need a complete, to the very end, enumeration - to all mats, stalemates, triple repetitions and other endings of the game according to chess rules? After all, if the algorithm leads to positions that are not required on this tree, then perhaps this entire tree does not need to be considered. Notice to yourself that in a disposition where White checkmates in one move, you can build the same infinite tree, but you don’t need to consider it, but it’s enough to find this one and only move. Maybe the situation is the same in chess in general? In general, the algorithm of enumeration, enumeration of options is related to so many tasks solved by a person that if we could organize it in some very original way, then it would, in a sense, be like the invention of a wheel for humanity - one of fundamental discoveries. So, enumeration could be, and maybe it is, the wheel of artificial intelligence.

- In one of the articles about artificial intelligence, I read that intelligence is the ability to understand and choose. Naturally, it is very difficult to teach a computer to choose from a variety of options. But surely some solutions specific to chess are possible?

- Yes Yes. This problem had to be solved quickly and efficiently, and in chess they quickly came to the following theoretical formulation of the question: let's look not at an infinite number of moves, but only a few moves ahead. Let's say we look 5 moves ahead. This is a lot. If you love chess and 5 moves seems not enough for you, then let's take 10. And then the machine for 10 moves, 20 half-moves ahead will not make mistakes in anything and guarantees that after 10 moves you will have no fewer pieces. It is clear that we are dealing with a strong playing machine. So the game tree will have to be reduced and the problem solved in a much more limited space. Another question is that they try to consider this tree not completely, with the help of mathematical pruning methods. I already talked about one of them: if there is a checkmate in one move, there is no need to look at other options. Other algorithms are heuristic, not exact. On average, they work correctly, many are absolutely accurate, but they can be wrong. For example, we can go through not all the moves, but only the capture, and calculate them much ahead, because there are few captures. The overall depth of the moves is small: you can't eat more than thirty-two pieces. Therefore, the lengths of the chains are small and there are few branches. Of course, it is clear that one cannot build a game on captures alone, there must be some positional considerations. The combination of forcing (capture, check) and positional considerations, as well as a certain depth of enumeration, is the basis of all existing algorithms, and it does not change much. Another question: how to select those moves that I will consider further? Is it based only on simple formal criteria (capture, check) or is it to link these moves, as chess players like to say, with a plan, to come up with some kind of chains that have some kind of common property? In any case, a lot of serious works with practical application have been written about this. It is not for nothing that rather reputable companies are engaged in the creation of chess programs.

– And when did the first chess programs appear?

- Real chess programs first appeared somewhere in the late 50s in America, and then somewhere in the early 60s - in our country. The programs were very weak, because then there were both extremely primitive machines and our thinking, which was not yet accustomed to novelty. We got involved in this business around 1963. Then on our domestic cars there were some matches. In my opinion, in 1967 there was the first match between the USSR and the USA. It was called that, although, of course, it took place between two teams, and not countries. It was a match between our program, developed at the Institute of Theoretical and Experimental Physics, and the program of John McCarthy, a very famous person in the computer world, one of the creators of programming languages, who was then fond of chess programs. The moves were transmitted by telegraph, because then there were no networks.

- And who won?

– We then won 3:1. Played 4 games. A move was made a day, because the Americans had more powerful and deep programs that thought for a long time, and we played on different versions of programs that thought both quickly and slowly. Our win was our first achievement. This direction began to develop gradually and became especially active in the 70s. Around 1974, the first World Chess Championship was held in Stockholm. About eight programs participated, including ours. And then we also won and became the first world champions. Since then, World Championships have been held regularly, every 3 years. We participated in them 2 more times - in 1977 and in 1980. We did not win Lavrov then, because in 1977 we shared the 2nd and 3rd places (many chess programs participated, there were even regional selections), and in 1980 - 4th and 5th place. In general, they slowly rolled back. The fact is that by this time there was already a huge progress in computing, and we were still playing on computers that were rather outdated. And by 1980, it became clear to us that competing on the machines on which we work had lost all meaning, and in general, work in the field of chess programs began to come to naught in Russia. Although there were quite a lot of interesting theoretical works. A little later, they created the first, perhaps, program that went around the world, she knew how to absolutely accurately play a complex endgame, that is, a queen and a pawn against a queen, or a rook and a pawn against a rook. The program simply considered such endgames to the end, i.e. in any position it gave an ideally correct move. The algorithm was built on principles slightly different from simple enumeration, on a complete inspection of the entire set of positions. Well, and then some works of this nature were made in chess. And then we said goodbye to the practical game, because the differences in speeds were already hundreds of times. But the championships continued, and the development of chess programs moved to a whole new level, as soon as everything moved to the PC. As a result of widespread commercialization, huge amounts of money began to be invested in chess programs, everything was immediately classified. And earlier they belonged to scientists who, if not forced on purpose, do not hide their achievements, but, on the contrary, propagate them. In 1980, we felt for the first time that it was time for commercial programming. This world is, of course, unique. Firstly, because money is invested in it, and secondly, because money is extracted from it. Although there are magazines on chess programs, but in the last 15 - 17 years, the real exchange of ideas has greatly diminished, because on the PC they have become a huge business.

– But commerce stimulates the development of the chess software market, doesn't it?

- Previously, computer competitions were timed to coincide with computer technology forums. There is such an organization - IFI (International Federation for Informatics) and, usually, world championships were timed to coincide with its congress. Now they have become absolutely independent events, quite prestigious. There are hundreds and hundreds of such programs. The very level of programming and the level of our knowledge is already such that it is not the slightest difficulty to make a simple chess program. This is normal student work. I just entrust it to some student. Beating a chess program has become, so to speak, a commonplace.

– But, as always, the lower level becomes simpler, while the higher one becomes more complicated?

- That's it. Therefore, the latest programs, those that are now winning, in particular, the program that defeated Kasparov, have become much stronger. The search depth has grown significantly and, of course, this is the result of our mathematical advances, and partly just the progress of computer technology. After all, if earlier consideration of 1000 positions per second was considered a lot, now in those trees that we have already talked about, more than a million positions are considered. And an extra million is several levels of moves with the right selection. And each level of search depth greatly enhances the program. Each level one move forward is approximately a rank, and, say, a search depth of four moves is the third rank, and five moves is already the second rank. When we reach the level of 11–13 moves, this is a master level and it is quite difficult to play with the machine further. Of course, the Americans are now leading, because they know how to invest big money in such things.

– Any artificial intelligence program for decision-making needs not only heuristic mechanisms, but also some kind of knowledge base. What is the relationship between the knowledge base and algorithms that generate positions in chess programs?

- No one can say for sure, because this is a subject of speculation. There were programs strong enough with just minimal knowledge, deliberately minimal, specifically to see what could be squeezed out of pure mathematics. At some point, this was due to commercialization, and especially to the fact that they began to make the most powerful programs - it doesn’t matter at the expense of what. But partly due to the fact that working with embedded knowledge is an independent task, there are a lot of them. First of all, a huge directory was created. Now directories are hundreds of thousands of positions. Then a lot of chess intelligence is always invested in evaluating positions. It comes down, of course, to game material, which is trivial, and to some positional factors. So, positional factors are purely chess intelligence, which, of course, is programmed, but here a lot of it is laid down and it is constantly being improved. And the more factors are invested there, the stronger the program. In a sense, the ability to evaluate the position and the depth of enumeration are interchangeable things. If we were able to evaluate the position ingeniously, then it would be enough for us to try all the first moves. This is like an extreme example. It is clear that a better position estimate has a correspondingly greater effect on the search depth. This is the second, fundamental method. There are quite a few programs where chess intellect is embedded in the choice of the options under consideration, that is, some purely chess considerations, some plans. There are quite a few such considerations, which limits the range of enumeration. The scope of their action is not very wide, and intellectual-chess-specific data slows down enumeration. By the way, it was precisely for intellectual things that Botvinnik once advocated very strongly. He was a great enthusiast of machine chess and contributed some ideas to it. Although he never managed to create a working program, nevertheless, his authority was then very high. So, he was very upset that, in general, the direction was not as "intellectual" as he would like, and a very limited amount of purely chess knowledge was invested in the programs.

– What about specialized chess computers? They, apparently, act precisely by the method of generation?

- Of course of course. First, in the sense of generation, enumeration is schematic. Secondly, any tables of positions are no less important, because in chess the repetition of positions is very high. You go E4E6D4 or D4E6E4 - the position will be the same, and it's only 3 half-moves. And when we start to go deeper, the repeatability of positions is very high. Thirdly, the technical area. In fact, at one time we built theories about for which positions local changes fundamentally cannot lead to a change in forced options, how to create some kind of templates. The templates of such options fit well into various purely technical schemes of a computer. Of course, reference diagrams are very important.

– Are there any means to create a universal mental apparatus in which one could put a knowledge base - no matter chess positions or anything else, the rules by which one must work with this knowledge - and get adequate results from it?

- It is clear that in terms of constructiveness, such a task cannot be solved today, it is not relevant. Although many intellectual tasks are now being solved, such as, for example, text recognition. You can put a sheet of text into the scanner and get it on the screen in Word. He will read himself, each letter is recognized. In fact, we have advanced in many intellectual tasks. Some of them have already been solved, others are being solved. In some ways it turns out relatively better than with the participation of a person, in some ways it is even worse. Many practical examples can be given. As for the universal artificial thinking mechanism, this is more of a philosophical problem than a practical one. After all, even for such a simple game as chess, it took us 30 - 40 years to actually achieve something. Every philosophy is based on opinions. Everyone thinks that he is right, and maybe everyone is right in his own way. For example, all my life I have dealt with artificial intelligence and I believe that the human brain is nothing more than a large computer, therefore, it cannot be said that it is fundamentally impossible to create an analogous one. The question is in its power, speed characteristics, in filling it with knowledge. There is nothing incomprehensible here. This is my personal point of view. But there are other opinions as well. Of course, if we recognize the divine nature of man, then we already have to choose one of two epistemological options. Or yes, we have a divine nature, but it is knowable. In this case, we will not be able to truly reproduce what the Lord God was able to do, but at least we will be able to at least partially recreate His creations. Or we stand on the position of agnosticism, and then it is unknowable, and the question is completely removed. It turns out that the human brain solves some problems - and here no one has any doubts. But we cannot catch up with the brain, because, on the one hand, it was created by God, and on the other hand, we are not able to know it. All three positions are associated with faith, since in reality it is not necessary to know all the functions of the brain. If we make a machine as powerful as the brain, then it does not need to think like the brain. She will work differently.

– In psychology, as far as I know, the intellectual development of a person is determined by three criteria: the ability to abstract, create an intellectual range, and something else... To what extent are these possibilities realized in artificial intelligence and are they realized at all?

- There are a lot of programs that are specifically aimed at creating concepts that abstract from the existing factual material. Such programs work well. Another question is that a person is able to create these concepts, as it were, according to his own laws, which he invents for himself. All our attempts to translate these laws of his into the language of the algebra of logic turn out to be futile. A person has a much more powerful thinking mechanism that we simply do not know. We can't do anything "at all". We create the formulations we need, but we cannot "express" them in exact machine problems. Everything is reduced to mechanical problems with difficulty, and even if it is reduced, then slowly. Probably, we do not yet know more direct ways to achieve the goal. Anything can be put into a computer. The question is that a person is able to manipulate this knowledge all the time, but he still does not know how to make a machine do the same due to the limited volume and speed of data.

“But maybe it doesn’t make any sense to force the machine to manipulate knowledge?”

– Both immoral and constructive aspects are touched upon here. We are still far from the rebellious machines. For my age, and for yours, too, there will be enough calmness for sure. Even in limited areas, we have not yet learned how to make the machine manipulate problems, even those that it can solve. We set a task, and she thinks only on command.

– Vladimir Lvovich, tell me, if it were the dawn of computer technology again, would it be worth doing chess programs? Were they really that conducive to progress?

– After all, chess expands our horizons. In chess programs, tasks are set, the result is visible, we evaluate it. Still, there must be many solved, interesting problems, which contributes to progress in computer technology.

Photos from open sources

The new artificial intelligence has become the best chess player on Earth in just 4 hours of training! (website)

Do you remember what a sensation the Deep Blue chess supercomputer made in 1996 when it won the first game against the Russian champion Garry Kasparov? Despite the fact that our compatriot nevertheless won this game, even then it became clear that artificial intelligence is rapidly progressing and will someday become the best chess player, after which it will be useless for people to play with the program. The only question left was when that would happen.

Representatives of the well-known corporation "Google" said that this time has finally come. According to experts, the AlphaZero neural network developed by them in just 4 hours of self-study turned into the most virtuoso and flawless chess player in the history of this game. A super-powerful artificial intelligence learned to play chess, knowing only its rules. After playing with itself for 4 hours, the robot learned to play perfectly, easily defeating the Stockfish chess program, which was considered the most perfect before. Computers played 100 games - AlphaZero managed to win 28 of them and draw the remaining 72. An advanced neural network that mimics the work of the human brain is able to take risks and even use a kind of intuition.

It is no longer necessary to dream of victory over artificial intelligence

Earlier "AlphaZero" models learned the game by watching live chess players. The developers assumed that this would help artificial intelligence to better understand the strategies of the game. In fact, it turned out that watching people only slows down the development of the program. When the neural network was left to its own devices, its abilities skyrocketed. Now Google engineers are thinking about how to apply such technologies for real benefit to mankind, since a chess game, even the most virtuoso one, has no practical purpose.

In 1968, the famous David Levy made a bet that no program would beat him for the next decade. All this time, the grandmaster was constantly competing with various chess computers and each time he beat them. In 1978, he defeated Chess 4.7, the strongest program at the time, winning a bet. Unfortunately, these days there will be no such interesting fights - we now have to learn only about how one fantastic neural network defeated another. Living chess players can no longer even dream of defeating such monsters. And this is just the beginning of such AI victories over humans…

culture. Dissertation. Cand. Ped Sciences. Rostov-on-Don. 2003.

2. Azarova E.A. Destructive forms of family education, topical problems of our time, crimes of recent times: spiritual, moral and forensic aspects. - Rostov-on-Don: Publishing House of the Russian State Pedagogical University, 2005.

3.Gabdrev GSH. The main aspects of the problem of anxiety in psychology // School psychologist. - 2004. - N ° 8. - S. 9.

4. Enikolopov S.N. Problems of family violence // Problems of psychology. -2002. -#5-6.

5. Tseluiko V.M. Psychology of a dysfunctional family: A book for teachers and parents. - M.: Publishing house VLADOS-PRESS, 2003.

6. Shapar V.B. Practical psychology. Psychodiagnostics of relations between parents and children. - Rostov n / a: Phoenix, 2006.

© Azarova E.A., Zhulina G.N., 2016

A.I. Alifirov

cand. ped. Sciences, Associate Professor, RSSU, Moscow, Russian Federation

I.V. Mikhailova Cand. ped. Sciences, Associate Professor, RSSU, Moscow, Russian Federation

"ARTIFICIAL INTELLIGENCE" IN CHESS

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The article discusses the genesis of the use of software and hardware capable of carrying out intellectual activity comparable to the intellectual activity of a person.

Keywords

Computer technologies in chess, chess programs, chess.

Today, the term "artificial intelligence" (AI) refers to the theory of creating software and hardware capable of carrying out intellectual activity comparable to human intellectual activity. When solving practical problems, they most often use the task from the list, while considering that if a computer system is able to solve these problems, then it is an AI system. Often this list includes playing chess, proving theorems, solving diagnostic problems on an initial incomplete data set, understanding natural language, the ability to learn and self-learn, the ability to classify objects, and the ability to generate new knowledge based on the generation of new rules and regularization models. knowledge .

One of the most important problems of the new science - cybernetics was the problem of how to improve management, how to improve decision-making. One of the founders of cybernetics C. Shannon proposed to formalize and program chess in order to use a chess computer as a model for solving similar control problems. The authority of K. Shannon was so great that his ideas immediately laid the foundation for a new scientific direction. The ideas of K. Shannon were used in the works of A. Turing, K. Zuse, D. Prince.

Author of information theory. K. Shannon, wrote: "The chess machine is ideal to start with, because (1) the task is clearly defined by permissible operations (moves) and the ultimate goal (checkmate); (2) it is not too simple to be trivial, and not too difficult to obtain a satisfactory solution; (3) believe that chess requires "thinking" for skillful play, the solution of this problem will lead us either to admire the ability of mechanized thinking, or to limit our concept of "thinking"; (4) The discrete structure of chess fits well with the digital nature of modern computers."

Later, chess became the subject of a competition between natural and artificial intelligence, and a number of matches were played by the world's leading chess players against computers. In 1995, in an interview with the popular Wired magazine, G.K. Kasparov outlined his view of the game of chess: "Chess is not mathematics. It is fantasy and imagination, it is human logic, not a game with a predictable result. I don't think that theoretically the game of chess can fit into a set of formulas or algorithms." Two years later, the DEEP BLUE supercomputer, having defeated the 13th world champion G.K. Kasparova in a rematch of six games, removed the question of the possibilities of chess artificial intelligence from the agenda. DEEP BLUE kept in memory a complete database of all games and analyzed strategy by calculation only. After the match, G.K. Kasparov changed his point of view, admitting that: "Chess is the only field where one can compare human intuition and creativity with the power and the machine." The match changed the course of development of both classical and computer chess. Artificial intelligence assistance has become widely used in the training system. DI. Bronstein in his book "David vs. Goliath" (2003) wrote: "Botvinnik believed that chess is the art of analysis, and the time of lone improvisers like Andersen, Morphy, Zuckertort is gone forever. Looking at modern chess, we must admit that Botvinnik turned out to be right. The "computer boys" took his idea of ​​the need for home analysis to the point of absurdity. They do not even hide the fact that they are polishing opening variations to a clear result. At the tournament in Linares (2000), the Hungarian Leko admitted without a shadow of embarrassment that the entire game with Anand was on his computer!".

List of used literature:

1. Alifirov A.I. Career guidance work in secondary schools by means of chess / Alifirov A.I. // Problems of development of science and education: theory and practice. Collection of scientific papers based on the materials of the International Scientific and Practical Conference August 31, 2015: in 3 parts. Part II. M.: "AR-Consult", 2015 - S. 13-14.

2. Mikhailova I.V., Alifirov A.I. Tactical actions of chess players / Mikhailova I.V., Alifirov A.I. // Results of scientific research Collection of articles of the International scientific-practical conference. Managing editor: Sukiasyan Asatur Albertovich (February 15, 2016) at 4 h. P/3 - Ufa: AETERNA. -2016.S. 119-121.

3. Mikhailova I.V., Alifirov A.I. Theoretical and methodological foundations of the method of thinking by schemes of chess players / Mikhailova I.V., Alifirov A.I. // Results of scientific research Collection of articles of the International scientific-practical conference. Managing editor: Sukiasyan Asatur Albertovich (February 15, 2016) at 4 h. P/3 - Ufa: AETERNA. - 2016. S. 123-125.

4. Mikhailova I.V. Training of young highly qualified chess players with the help of computer chess programs and the "Internet": author. dis. ... cand. ped. Sciences: 13.00.04 / Mikhailova Irina Vitalievna; RSUPC. - M., 2005. - 24 p.

© Alifirov A.I., Mikhailova I.V., 2016

UDC 378.046.2

A.I. Alifirov

Candidate of Pediatric Sciences, Associate Professor of RSSU, Moscow, RF V.V. Fedchuk, Ph.D.

LLC "Prosperity", senior instructor methodologist, Moscow, Russian Federation STUDY OF THE LEVEL OF PHYSICAL HEALTH OF ADOLESCENTS

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The article deals with the problem of physical health of adolescents and the influence of various factors