商业电脑游戏的进化行为测试

Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI:10.1109/CEC.2004.1330847

B. Chan, J. Denzinger, D. Gates, Kevin Loose, J. W. Buchanan

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引用次数: 44

摘要

我们提出了一种使用行为进化学习来改进商业电脑游戏测试的方法。在确定了不想要的结果或游戏行为之后，我们建议开发一种方法来衡量一系列游戏状态离不想要的行为有多近，并在GA的适应度函数中使用这些方法来处理动作序列。这允许我们找到产生不必要行为的动作序列(如果它们存在的话)。我们在《FIFA-99》游戏中对该方法进行了实验评估，并将进球作为不想要的行为，结果表明该方法能够找到这样的动作序列，允许轻松再现关键情况并改进测试游戏。

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Evolutionary behavior testing of commercial computer games

We present an approach to use evolutionary learning of behavior to improve testing of commercial computer games. After identifying unwanted results or behavior of the game, we propose to develop measures on how near a sequence of game states comes to the unwanted behavior and to use these measures within the fitness function of a GA working on action sequences. This allows to find action sequences that produce the unwanted behavior, if they exist. Our experimental evaluation of the method with the FIFA-99 game and scoring a goal as unwanted behavior shows that the method is able to find such action sequences, allowing for an easy reproduction of critical situations and improvements to the tested game.

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Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)

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