Applying Reinforcement Learning for the AI in a Tank-Battle Game
Yung-Ping Fang, I‐Hsien Ting · Journal of Software · 2010
Reinforcement learning is an unsupervised machine learning method in the field of Artificial Intelligence and offers high performance in simulating the thinking ability of a human. However, it requires a trial-and-error process to achieve this goal. In the research field of game AIs, it is a good approach that can give the non-player-characters (NPCs) in digital games more human-like qualities. In this paper, we try to build a Tank-battle computer game and use the methodology of reinforcement learning for the NPCs (the tanks). The goal of this paper is to make this game become more interesting due to the enhanced interactions with the more intelligent NPCs.