Assessing Believability
Assessing Believability
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评估可信度
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Noor Shaker
中科院分区：
文献类型：
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作者：
J. Togelius;Georgios N. Yannakakis;S. Karakovskiy;Noor Shaker
我们讨论了非玩家角色(NPC)可信或像人类意味着什么，以及我们如何准确地评估可信度。我们认为，参与式观察，即人类评估可信度的游戏的一部分，容易产生扭曲效应。对于许多游戏，通过比较和排名玩游戏的人类和非人类代理的性能，不参与游戏的外部观察者可能会做出更公平(或至少是补充)的评估。这一评估理念体现在最近举行的马里奥AI锦标赛的图灵测试赛道上，非专家旁观者评估了几个特工和扮演超级马里奥兄弟版本的人类的人性化程度。我们分析了这次比赛的结果。最后，我们讨论了通过调整游戏内容而不是NPC控制逻辑来形成可信度模型和最大化可信度的可能性。
We discuss what it means for a non-player character (NPC) to be believable or human-like, and how we can accurately assess believability. We argue that participatory observation, where the human assessing believability takes part in the game, is prone to distortion effects. For many games, a fairer (or at least complementary) assessment might be made by an external observer that does not participate in the game, through comparing and ranking the performance of human and non-human agents playing a game. This assessment philosophy was embodied in the Turing Test Track of the recent Mario AI Championship, where non-expert bystanders evaluated the humanlikeness of several agents and humans playing a version of Super Mario Bros. We analyze the results of this competition. Finally, we discuss the possibilities for forming models of believability and of maximizing believability through adjusting game content rather than NPC control logic.