標題: 以基因演算法進行星海爭霸之單位行動選擇最佳化
Optimization of Action Selection in StarCraft with Genetic Algorithm
作者: 許維倫
陳穎平
Hsu, Wei-Lun
Chen, Ying-Ping
資訊科學與工程研究所
關鍵字: 基因演算法;最佳化;即時戰略遊戲;遊戲人工智慧;genetic algorithm;optimization;real-time strategy game;game AI
公開日期: 2016
摘要: 電腦遊戲從未在電子資訊科技產業中缺席,在這麼多遊戲中即時戰略遊戲一直都是電競比賽的熱門焦點,而星海爭霸可以視為即時戰略遊戲的代表作,可惜目前市面上的即時戰略遊戲,大多利用特殊方法造成玩家與電腦之間條件不對等,達到難易度的調整。所以我們提出了一個構想,使得星海爭霸的遊戲人工智慧變得更強,讓即時戰略遊戲變得更好玩。以外在論文的最後列出了幾個未來可以供人使用的研究方向,希望此研究成為更強的星海爭霸遊戲人工智慧的基石。
Computer game have never been absent in Information technology industry. In so many type of game, the real-time strategy(RTS) game has always been the focus of gaming competitions and StarCraft can be regarded as a masterpiece of real-time strategy game. Unfortunately, most of the real-time strategy game AI can't achieve the same level of player. In order to make RTS game better, we attempt to develop a mechanism which is able to optimize action selection in StarCraft. Because we hope this study become the cornerstone of a great StarCraft AI, we listed some future research directions at the end of this paper.
URI: http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070356066
http://hdl.handle.net/11536/138810
Appears in Collections:Thesis