DocumentCode
3455691
Title
Applying Reinforcement Learning for Game AI in a Tank-Battle Game
Author
Fang, Yung-Ping ; Ting, I-Hsien
Author_Institution
Dept. of Inf. Manage., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
fYear
2009
fDate
7-9 Dec. 2009
Firstpage
1031
Lastpage
1034
Abstract
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.
Keywords
computer games; unsupervised learning; artificial intelligence; digital games; game AI; intelligent nonplayer characters; reinforcement learning; tank-battle computer game; trial-and-error process; unsupervised machine learning method; Application software; Artificial intelligence; Computational modeling; Delay; Humans; Information management; Learning systems; Least squares approximation; Legged locomotion; Machine learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
Conference_Location
Kaohsiung
Print_ISBN
978-1-4244-5543-0
Type
conf
DOI
10.1109/ICICIC.2009.114
Filename
5412307
Link To Document