International Journal of Advanced Research in Computer and Communication Engineering

Abstract: The integration of advanced Artificial Intelligence (AI) and Machine Learning (ML) technologies is fundamentally transforming interactive entertainment by enabling the development of non-Player Characters (NPCs) that are dynamic and highly responsive to player actions and evolving game environments. This study explores various AI techniques used in NPC development, including Deep Learning, Reinforcement Learning, Natural Language Processing (NLP), and Behavioral Cloning. It examines how these technologies enable NPCs to exhibit sophisticated behaviors, learn from player interactions, and adapt to changing game conditions. Key findings are derived from a comparative case study of Grand Theft Auto V (GTA V) and Red Dead Redemption 2 (RDR2), which reveals a critical trade-off between scale (GTA V prioritizes scale) and depth (RDR2 emphasizes authenticity). The research concludes that hybrid AI architectures combining multiple machine learning approaches yield superior NPC performance, establishing a paradigm shift toward creating authentic virtual worlds that respond intelligently, remember meaningfully, and evolve naturally over time, thereby setting new standards for player immersion and engagement. The document also discusses the technical challenges involved in implementing AI-driven NPCs, such as computational complexity, real-time processing constraints, and maintaining behavioral consistency.

Downloads: | DOI: 10.17148/IJARCCE.2025.141013