標題: Game team balancing by using particle swarm optimization
作者: Fang, Shih-Wei
Wong, Sai-Keung
資訊工程學系
Department of Computer Science
關鍵字: Artificial neural network;Particle swarm optimization;Game balance;Role-playing game;Team balancing system
公開日期: 1-十月-2012
摘要: Game balancing affects the gaming experience of players in video-games. In this paper, we propose a novel system, team ability balancing system (TABS), which is developed for automatically evaluating the performance of two teams in a role-playing video game. TABS can be used for assisting game designers to improve team balance. In TABS, artificial neural network (ANN) controllers learn to play the game in an unsupervised manner and they are evolved by using particle swarm optimization. The ANN controllers control characters of the two teams to fight with each other. An evaluation method is proposed to evaluate the performance of the two teams. Based on the evaluation results, the game designers can adjust the abilities of the characters so as to achieve team balance. We demonstrate TABS for our in-house MagePowerCraft game in which each team consists of up to three characters. (C) 2012 Elsevier B.V. All rights reserved.
URI: http://dx.doi.org/10.1016/j.knosys.2012.02.017
http://hdl.handle.net/11536/16820
ISSN: 0950-7051
DOI: 10.1016/j.knosys.2012.02.017
期刊: KNOWLEDGE-BASED SYSTEMS
Volume: 34
Issue: 
起始頁: 91
結束頁: 96
顯示於類別:期刊論文


文件中的檔案:

  1. 000309093000011.pdf