摘要
在游戏开发过程中,场景设计作为游戏开发的重点,如果都由设计师逐一设计将花费大量的时间和资本,而且玩家黏着度低。本文提出一种基于数据挖掘和融合技术的游戏关卡自动生成方法。该方法首先利用布尔逻辑与粗糙集理论相结合的离散化方法对游戏玩法数据进行预处理,并提出一种基于信息增益的属性约简算法消除冗余属性;接着利用决策树ID3算法建立一个游戏难易程度的评估模型,构造决策树;然后利用数据融合D-S算法得到体现玩家行为的数据,并结合决策树得到对于玩家的难易程度;最后根据难易程度获得游戏关卡参数,并自动生成游戏关卡。以推箱子游戏做的实验结果表明,该方法有效降低了开发成本并提高了游戏的可玩性。
In game development, if scene design as the focus is designed one by one, a lot of time and capital will be spent, and players stick low degree. Therefore, a game level automatic generation method based on data mining and data fusion technology is presented. Firstly, the method preprocesses the game play data by using the discretization of Boolean logic combined with rough set theory, puts forward an attribute reduction algorithm based on information gain to eliminate the redundant attributes. Second- ly, a decision tree is constructed by using the ID3 algorithm to build an evaluation model of game difficulties. Then the D-S data fusion algorithm is used to get the data reflecting the players behavior, and the data is processed with the decision tree to get the difficulty level of the game for players. Finally, the game level parameters are modified to automatically generate the game level according to the difficulty level. By the experiment of Sokoban game for example, the results show that the method is effective to reduce development cost and to improve playability.
出处
《计算机与现代化》
2013年第4期10-14,共5页
Computer and Modernization
基金
中国民航信息技术科研基地开放课题基金资助项目(CAAC-ITRB-201209)
国家自然科学基金资助项目(61070202)
关键词
数据挖掘
数据融合
属性约简
游戏关卡
自动生成
data mining
data fusion
attribute reduction
game level
automatic generating
