SYSTEMATIC ANALYSIS OF MAZE GENERATION ALGORITHMS IN INTERACTIVE GAME ENVIRONMENTS

Labyrinths in video games serve not only as navigation tools but also as complex design elements that combine technical, aesthetic, and gameplay functions. The use of procedural generation, interactive elements, and adaptive systems enables innovative approaches to construct virtual spaces. The purpose of this study is to develop a systematic classification of algorithms for the procedural generation of labyrinths for use in video game development and to determine their functional characteristics, advantages, and limitations, considering technical and game design requirements. The relevance of the research lies in the growing importance of procedural content in modern game development, which enhances replayability, adaptability, and reduces the cost of manual level design. This study presents a review and comparative analysis of modern maze generation algorithms, including classical approaches (DFS, Prim’s, Kruskal’s, Eller’s, Wilson’s, Aldous-Broder), cellular automata (Rule 4/5, Conway’s Game of Life, Maze CA, Mazectric, Hybrid CA), noise functions (Perlin, Simplex, Worley), fractal systems (L-systems, Hilbert curves), and machine learning-based algorithms (neuroevolution, Wave F