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http://dx.doi.org/10.7583/JKGS.2011.11.6.061

NPC Control Model for Defense in Soccer Game Applying the Decision Tree Learning Algorithm  

Cho, Dal-Ho (SangMyung University Dept of Computer Science, Graduate School)
Lee, Yong-Ho (SangMyung University Dept of Computer Science, Graduate School)
Kim, Jin-Hyung (Division of Digital Media, College of Computer Software & Digital Media)
Park, So-Young (Division of Digital Media, College of Computer Software & Digital Media)
Rhee, Dae-Woong (Division of Digital Media, College of Computer Software & Digital Media)
Abstract
In this paper, we propose a defense NPC control model in the soccer game by applying the Decision Tree learning algorithm. The proposed model extracts the direction patterns and the action patterns generated by many soccer game users, and applies these patterns to the Decision Tree learning algorithm. Then, the proposed model decides the direction and the action according to the learned Decision Tree. Experimental results show that the proposed model takes some time to learn the Decision Tree while the proposed model takes 0.001-0.003 milliseconds to decide the direction and the action based on the learned Decision Tree. Therefore, the proposed model can control NPC in the soccer game system in real time. Also, the proposed model achieves higher accuracy than a previous model (Letia98); because the proposed model can utilize current state information, its analyzed information, and previous state information.
Keywords
Decision Tree; Soccer Game; Machine Learning; Game AI;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
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