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银河军备竞赛（GAR）：在多人在线视频游戏中自动生成内容
Galactic Arms Race (GAR): Automatic Content Generation In a Multiplayer Online Video Game |
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| 课程网址: |
http://videolectures.net/ijcai09_hastings_gar/
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| 主讲教师: |
Kenneth O. Stanley, Ratan Kumar Guha, Erin J. Hastings
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| 开课单位: |
中央佛罗里达大学
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| 开课时间: |
2009-06-20
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| 课程语种: |
英语
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| 中文简介: |
该视频展示了一种名为cgNEAT的新AI算法自动生成视频游戏中的内容。为了证明这一点新技术，我们创造了一个近乎商业化的质量游戏银河系统（GAR）完全由武器系统组成游戏本身发明的。 cgNEAT方法，简称
内容生成增强拓扑的NeuroEvolution，不断发展新型武器（由人工神经网络控制）改变过去最流行的武器。就这样，一个进化过程使算法探索空间玩游戏时的武器，产生永无止境的供应新颖而实用的内容。目的是表明AI可以足够复杂，可以在没有游戏的情况下产生一些内容通过观察玩家喜欢的东西，对艺术家或程序员的需求在过去。该视频展示了实际游戏玩法的剪辑展示了令人惊讶的各种引人注目的武器游戏本身。它还更多地阐明了基础AI技术通过行动而不是通过言语。有关GAR的更多信息，将于今年春天发布，
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| 课程简介: |
This video showcases a new AI algorithm called cgNEAT that automatically generates content in video games. To demonstrate this new technique, we created a near-commercial-quality game called Galactic Arms Race (GAR) in which the weapons systems are entirely invented by the game itself. The cgNEAT method, which is short for content-generating NeuroEvolution of Augmenting Topologies, evolves new weapons (which are controlled by artificial neural networks) by varying the most popular weapons of the past. In this way, an evolutionary process causes the algorithm to explore the space of weapons as the game is played, producing a never-ending supply of novel and functional content. The aim is to show that AI can be sophisticated enough to produce some of the content in games without the need for artists or programmers, by observing what players liked in the past. The video presents a montage of actual gameplay that demonstrates the surprising variety of compelling weapons invented by the game itself. It also explicates the underlying AI technology more through action than through words. For more information on GAR, which will be released this Spring,
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| 关 键 词: |
cgNEAT新型AI自动算法; 游戏内容; 内容生成增强拓扑
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| 课程来源: |
视频讲座网
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| 最后编审: |
2021-12-22：liyy
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| 阅读次数: |
48
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