论文信息 - Applying Reinforcement Learning for Game AI in a Tank-Battle Game

Applying Reinforcement Learning for Game AI in a Tank-Battle Game

Reinforcement learning is an unsupervised machine learning method in the area of Artificial Intelligence. It presents well performance in simulation of the thinking ability of human. However, it needs a trial-and-error process to achieve the goal. In the research field of game AI, it is a good approach to allow the non-player-characters (NPCs) of digital games to become more humanity. In this paper, we try to build a Tank-battle computer game and use the methodology of reinforcement learning for the NPCs (tanks). The goal of this paper is to make this game become more interesting from the enhanced interactions with these intelligent NPCs.

I-Hsien Ting | Yung-Ping Fang

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