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The Evolution of Artificial Intelligence and the Possibility of Its Application in Cyber Games View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Revista Amazonia Investiga Volume 9 - Issue 28 / April 2020 123 DOI: http://dx.doi.org/10.34069/AI/2020.28.04.15 The Evolution of Artificial Intelligence and the Possibility of its Application in Cyber Games Эволюция искусственного интеллекта и возможность его применения в кибериграх Received: January 28, 2020 Accepted: March 12, 2020 Written by: Eliseeva D. Yu.58 https://orcid.org/0000-0002-1593-352X Fedosov A. Yu.59 https://orcid.org/0000-0002-2621-2218 Agaltsova D. V.60 https://orcid.org/0000-0001-8892-2437 Mnatsakanyan O. L.61 https://orcid.org/0000-0001-9380-5497 Kuchmezov K. K.62 https://orcid.org/0000-0002-2550-5086 Abstract Аннотация Artificial intelligence, as a separate field of Искусственный интеллект, как отдельная область research, is currently experiencing a boom - new исследования, в настоящее время переживает methods of machine learning and hardware are подъём – появляются новые и совершенствуются emerging and improving, and the results achieved существующие методы машинного обучения, change the life of society. Machine translation, аппаратные средства, а достигнутые результаты handwriting recognition, speech recognition are меняют жизнь общества. Машинный перевод, changing our reality. The work of creating распознавание рукописного текста, unmanned vehicles, voice assistants and other распознавание речи уже повсеместная devices using these technologies is in an active реальность. Активно ведутся работы по созданию беспилотных автомобилей, голосовых process. The article examines the historical context помощников и прочих устройств, использующих of the artificial intelligence development, it данные технологии. В статье рассматривается evaluates the possibilities of its introduction into исторический контекст становления cyber games, as a safe and effective platform for искусственного интеллекта, оцениваются testing new methods of machine learning. The возможности его внедрения в киберигры, как promotion of such projects can increase the безопасную и эффективную площадку для reputation of development companies, ensure испытаний новых методов машинного обучения. increased user confidence in other products and, Продвижение подобных проектов способно with a competent marketing strategy, cause a повысить репутацию компаний-разработчиков significant public resonance among video game обеспечить повышение уровня доверия fans, providing the developer with economic profit. пользователей к остальной продукции и, при грамотной маркетинговой стратегии, вызвать Key Words: artificial intelligence, cyber games, весомый общественный резонанс среди machine learning, neural network, pattern поклонников видеоигр, обеспечив recognition. экономическую прибыль разработчику. Ключевые слова: искусственный интеллект, киберигры, машинное обучение, нейросеть, распознавание образов. 58 Senior Teacher, Russian State Social University, Moscow, Russia 59 Dr.Sc., Professor, Russian State Social University, Moscow, Russia 60 PhD, Associate Professor, Financial University under the Government of the Russian Federation Moscow, Russia 61 PhD, Associate Professor, Russian State Social University, Moscow, Russia 62 PhD, Associate Professor, Financial University under the Government of the Russian Federation, Moscow, Russia http:// www.amazoniainvestiga.info ISSN 2322 - 6307 Eliseeva, D. Yu., Fedosov, A. Yu., Agaltsova, D. V., Mnatsakanyan, O. L., Kuchmezov K. K./ Volume 9 - Issue 28: 123-129 / April, 2020 124 Introduction One of the interesting properties of society is the background in which many other scientists growth rate of its individual measurable played an important role. indicators at rates close to exponential progression. Such an effect can be seen in the Theoretical framework population, in economic indicators, in science. The authors of the first work on artificial F. Engels noted: «... science is growing at least as intelligence are Warenn McCallock and Walter fast as the population; science moves forward in Pitts - described a model consisting of artificial proportion to the mass of knowledge inherited neurons (a kind of symbiosis of the knowledge of from the previous generation» (F. Engels, 1968). physiology, logic and computational theory of In the modern world, the ways of interaction Alan Turing), which could calculate all possible between scientists are being improved, the work logical connections (McCulloch W.S., Pitts W., organization of large groups of researchers 1943). It has been suggested that such a model becomes possible, the natural consequence of can be trained - such a method was demonstrated this is the emergence of new areas of research, by Donald Hebb, his proposal is now called Hebb new sciences - either specifying individual training. classical sections, or arising at the junction of several research areas. As a result, within the Another important work is an article by framework of one generation, we can see the Computing Machinery and Intelligence by Alan formation of a new field of knowledge, which is Turing, which described: Turing test, principles becoming one of the leading and determining in of machine learning, genetic algorithms, society. A striking example was the Dartmouth reinforcement learning (Turing, 1950). seminar, which brought together in 1956 ten scientists from different fields of science For many years, scientists worked on creating working on similar issues, who received the artificial intelligence systems, high expectations name proposed by John McCarthy - artificial were placed on programs, but all of them solved intelligence. some small problem in their simulated “microcosm”, and when attempts were made to As far back as in the past centuries, philosophers create larger-scale projects, this approach did not argued on the topic of thinking, searched for work. The programs did not possess answers to questions - if there is any difference "intelligence", but sorted through all sorts of between mind and matter, and various fields of options and found the right ones - for complex science have created a theoretical machine, the problems a combinatorial explosion occurred, foundation which artificial intelligence stands on that is, the number of searches exceeded the now. For artificial intelligence, formalization of calculated powers. The problem was not only in three fundamental areas became important: logic the insufficient power of computers, but also in (George Boolean - Boolean logic), computation the poor elaboration of the theory - the (Church-Turing theorem) and probability theory accumulated experience and planning were (Bayes theorem, which underlies many machine inefficiently used. A very striking example: the learning methods). Economists, trying to development of machine translation of text. A lot understand how people make decisions to of money was invested in this project by the US achieve preferable results, have come to the National Research Council, but it all ended in creation and study of decision theory and game collapse. The program translated "word for theory. A logical continuation of the study was word", not considering the context, which was the study of operations, and a certain class of very important. As a result, funding programs sequential problems of decision-making were shut down, and artificial intelligence waited (Markov processes) was formalized in the work for several years of calm. of Richard Bellman. Interesting results were obtained by the work of neurologists - the The next surge of interest in artificial intelligence collaboration of simple neuron cells can lead to systems occurred in the period 1980-1986 and is the appearance of thinking, action and associated with the development of expert consciousness. The brain is consisted of billions systems. In these projects, the programs had a of neurons, therefore, to simulate its behavior, it knowledge base (rules), separated from requires the creation of many simple modules components that could carry out logical and the organization of their interaction - reasoning. The first such example is the Dendral computer technology has begun to solve this program, which has been successfully used for problem. All these achievements are only a scientific purposes. After a while, the first www.amazoniainvestiga.info ISSN 2322- 6307 Volume 9 - Issue 28 / April 2020 125 commercial expert system appeared - all these − training without a teacher, when there is successes increased the flow of funding from the data, but it is not marked up, or when it states and private capital, and artificial is difficult in principle to do this - the intelligence, in fact, became an industry. But the computer independently looks for story repeated itself. The subsequent calm was patterns; called the “winter of artificial intelligence”, − training with the partial involvement of although some groups of scientists did not stop a teacher - something in between the working. For example, in 1987, neural networks first two points; with back spread of error were developed, − reinforcement training - when there is evolutionary methods — genetic algorithms and no data, but the computer can interact genetic programming — were better studied. with a certain system and receive Around the same time, artificial intelligence rewards. became tougher based on exact calculations, the mathematical machine. The mechanism of human intelligence has not been fully studied, there is no exact list of The next stage of the revival occurred in the properties, the fulfillment
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