Implementation of artificial intelligence in "ToqyzQumalaq" mobile logic game

Abstract

This research paper delves into the implementation of artificial intelligence (AI) in the mobile logic game "ToqyzQumalaq," focusing on incorporating advanced algorithmic strategies to improve gameplay. The game's complexity and strategic depth present unique challenges in AI development, addressed through the integration of algorithms like Minimax, Alpha-Beta Pruning, Greedy, and Particle Swarm Optimization (PSO). The study emphasizes the creation of evaluation functions for these algorithms, ensuring AI efficiency and human-like decision-making. This aspect is vital for maintaining the strategic unpredictability essential to "ToqyzQumalaq." Extensive experimental testing against human players of various skill levels demonstrates the algorithms' effectiveness. These tests reveal the strengths and limitations of each algorithm, providing insights into their application in the game. This paper contributes to AI in gaming, highlighting the challenges and opportunities in developing AI for complex games. Its findings are relevant not only to game developers but also serve as an educational tool, showcasing the practical application of AI and algorithmic strategies.