This study aims to explore the application of artificial intelligence algorithms in the development of a simple 2D game called Cuypy using the Python programming language. Cuypy is designed to provide an interactive, educational, and challenging gameplay experience. Artificial intelligence is implemented to enhance enemy intelligence, game adaptability to player behavior, and overall system responsiveness. The development focuses on the integration of pathfinding algorithms and machine learning techniques to improve enemy strategy, enabling non-player characters to learn from player actions and adjust their behavior dynamically to increase the level of challenge over time. Additionally, this study emphasizes the use of reinforcement learning mechanisms that allow enemies to predict player movement patterns and automatically adapt their strategies. Pygame is utilized as the graphical library to build the user interface and animations, while Python serves as the main programming language supporting efficient AI implementation. The novelty of this research lies in the real-time behavioral adaptation of game enemies based on player interactions, a feature that is rarely explored in simple Python-based games. This study also highlights the integration of pathfinding algorithms to ensure more realistic, adaptive, and engaging enemy movements. Overall, the research contributes to the development of interactive Python-based games and provides insights into applying AI to simple educational games with automatically adjustable difficulty levels
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