The use of computer technology and artificial intelligence in the training of professional chess players

Abstract

The research is devoted to the analysis of the integration of computer technologies and artificial intelligence into the system of training high-level chess players. In the context of digitalization of sports and rapid progress in the field of computer analysis of chess positions, methodological approaches to the training process of grandmasters are being transformed. A multifactorial analysis of the influence of chess engines, training neural networks and analytical platforms on the qualitative indicators of the training process is carried out. The study is based on a comprehensive methodological approach, including a statistical analysis of the performance of 124 international chess players, an expert survey of 28 coaches of the highest category, and a comparative analysis of the effectiveness of various computer tools. A statistically significant correlation was found between the intensity of use of neural network analytical tools and an increase in the Elo rating (r=0.72, p<0.001). It has been established that the use of cloud-based analytical services helps to reduce the time required to master the opening schemes by 37.4% while increasing the accuracy of decisions. The effectiveness of integrated training complexes combining classical techniques with digital computer analysis tools and simulation of game situations has been proven. The results of the study form an updated paradigm of chess players' training in the era of artificial intelligence dominance and open up prospects for further digital transformation of the training process in intellectual sports.