Design and Development of an AI-Based Human-Like NPC with Context-Aware Dialogue and Adaptive Behavior for video Games

Description This research presents an AI-driven framework for developing human-like Non-Player Characters (NPCs) in Unity game environments. The proposed system combines machine learning, reinforcement learning, behavior modeling, and emotion-based decision-making to create adaptive NPCs capable of responding intelligently to player actions. Unlike traditional scripted NPCs, the proposed framework aims to improve realism by enabling dynamic behavior, learning from interactions, and context-aware decision-making. The paper discusses the system architecture, implementation methodology, NPC behavior design, learning mechanisms, and performance evaluation. Experimental results demonstrate the potential of the proposed approach to enhance player immersion and create more engaging gameplay experiences. This work contributes to the advancement of intelligent game AI and provides a foundation for future research on adaptive and human-like virtual characters. This is a preprint and has not yet undergone peer review. Feedback and comments are welcome.