Artificial intelligence applied to the evolution of FPS electronic games (Research, Society and Development, 2026)
The main objective of this review is to map and analyze how artificial intelligence (AI) has been used to enhance player experience in FPS games, with a focus on aspects such as the behavior of non-playable characters (NPCs), difficulty adaptation, immersion, realism, and personalization. Using a rigorous method based on Kitchenham’s guidelines, studies published between 2023 and 2025 were synthesized. The results demonstrate a clear transition from classical AI techniques, such as Finite State Machines (FSMs) and Behavior Trees (BTs), to advanced machine learning algorithms, notably deep reinforcement learning. The analysis shows that AI is a central pillar in the modernization of FPS games, directly impacting non-playable character (NPC) behavior, experience personalization through Dynamic Difficulty Adaptation (DDA), and the pursuit of greater immersion and realism. The study also identifies recurring technical challenges, such as high computational costs, the need for large datasets for training, and the complexity of debugging “black-box” models. Finally, emerging trends are discussed, such as the use of Large Language Models (LLMs) for natural dialogues and generative AI for dynamic content creation, pointing toward a future with increasingly intelligent and adaptive gaming experiences.