基于人工神经网络的mmog机器人检测系统

Kusno Prasetya, Z. Wu
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引用次数: 12

摘要

作弊是mmog中最大且持续存在的问题之一。作弊频率高的游戏肯定会失去对真正想玩游戏的玩家的吸引力。这就是为什么游戏供应商现在把防止作弊作为首要任务之一的原因。这只是一种作弊方式,但非常有效。有各种方法来防止作弊使用机器人。在本文中,我们研究了人工神经网络(ANN)从人类玩家中检测和识别机器人的潜力。我们首先假设一个bot在游戏玩法中总是以相似的模式行动。与此同时,拥有相似玩法模式的两名玩家却非常罕见。我们的实验结果支持了我们最初的假设,并为未来的研究提供了可能,以获得更好的结果。
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Artificial Neural Network for bot detection system in MMOGs
Cheating is one of the biggest and constant problems in MMOGs. Games with high frequency of cheating will surely lose its appeal to genuine players who want to play the game. This is the reason why game provider these days put cheating prevention as one of the top priorities. Bot is just one way of cheating, but very efficient one. There are various methods to prevent cheating using bot. In this paper, we examine the potential of Artificial Neural Network (ANN) to detect and recognize bot from human players. We start with the assumption that one bot always acts in the similar pattern in gameplay. Meanwhile, it is much more rarer to see 2 players with similar gameplay pattern. The result of our experiment supports our initial hypothesis with the potential for future research in order to get better results.
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