NPC Behavior in Games Using Unity ML-Agents: A Reinforcement Learning Approach

Machine learning is having a significant impact on video games, from speeding up the development of new games to the development of new methods in gaming. This study discusses the impact of using ML models in the development and improvement of video games. Examples cited in this paper relate to the ways in which NPCs behave. With the aid of Unity's ML-Agents toolkit, developers can create NPCs that respond to different strategies in real time. This makes the games more exciting and complex. The paper also outlines the possibilities of single-player games, such as first-person shooters and a role-playing game, to notice NPC behavior during the gameplay. In these gaming styles, RL frameworks can be applied to NPCs to enable them to learn and adapt to the environment to create an interactive experience for the player. The conclusions put an emphasis on the evolution of video games with the advent of ML tools; as predicted, NPC behavior becomes more intuitive and less expected.