Evolution of Algorithmic Techniques in Musical Compositions as a Prerequisite for the Integration of Artificial Intelligence into Art

The purpose of the article is to examine the evolution of algorithmic techniques in the domain of musical composition, as well as the methods of formalising musical structures. The methodology of the study incorporates analytical, structural-functional, and generalising approaches. Scientific novelty. This study builds on an assessment of the cultural significance of early experiments with compositional automation. These experiments gained expressive characteristics by the late 18th century and subsequently evolved through the emergence of the first systems of musical aleatoricism. Prominent computer music figures such as Max Mathews and Lejaren Hiller also contributed to this development. This study substantiates the evolutionary pathway from algorithmic composition techniques and musical structure formalisation methods to the advent of modern digital technologies. Conclusions. The formation and evolution of algorithmic techniques in musical composition have been the subject of much research, with many scholars examining the processes of musical structures formalisation within the context of technological progress. The history of systematic approaches to music creation demonstrates a gradual shift in compositional principles: from the isorhythmic techniques of the late Middle Ages and the experimental “musical games” of the Enlightenment to contemporary methods incorporating digital algorithms and artificial intelligence. Key stages in the evolution of algorithmic music are highlighted: the original concept of musical structures formalisation, which provided the foundation for further development of compositional techniques; the experimental algorithms of the 18th and 19th centuries, integrating stochastic methods and mechanical principles for musical sequences creation; and the digital revolution of the 20th century, which, through computer automation, facilitated the first experiments in music generation based on stochastic and deterministic models. The influence of these elements on the emergence of contemporary algorithms is evident, as they have expanded beyond the imitation of classical composers’ styles to the creation of autonomous musical compositions featuring novel creative approaches. It is substantiated that, after centuries of evolution, algorithmic composition techniques have now attained a new qualitative level through artificial intelligence.