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A Neurally Controlled Computer Game Avatar With Humanlike Behavior

机译:具有人性行为的中立控制计算机游戏头像

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This paper describes the NeuroBot system, which uses a global workspace architecture, implemented in spiking neurons, to control an avatar within the Unreal Tournament 2004 (UT2004) computer game. This system is designed to display humanlike behavior within UT2004, which provides a good environment for comparing human and embodied AI behavior without the cost and difficulty of full humanoid robots. Using a biologically inspired approach, the architecture is loosely based on theories about the high-level control circuits in the brain, and it is the first neural implementation of a global workspace that has been embodied in a complex dynamic real-time environment. NeuroBot's humanlike behavior was tested by competing in the 2011 BotPrize competition, in which human judges play UT2004 and rate the humanness of other avatars that are controlled by a human or a bot. NeuroBot came a close second, achieving a humanness rating of 36%, while the most human human reached 67%. We also developed a humanness metric that combines a number of statistical measures of an avatar's behavior into a single number. In our experiments with this metric, NeuroBot was rated as 33% human, and the most human human achieved 73%.
机译:本文介绍了NeuroBot系统,该系统使用以尖峰神经元实现的全局工作区体系结构,以控制Unreal Tournament 2004(UT2004)计算机游戏中的化身。该系统旨在显示UT2004内的类人行为,从而为比较人为和体现的AI行为提供了一个良好的环境,而没有完整类人机器人的成本和难度。使用受生物学启发的方法,该体系结构松散地基于关于大脑中高级控制电路的理论,并且这是在复杂的动态实时环境中实现的全局工作区的第一个神经实现。 NeuroBot的类人行为在2011年的BotPrize竞赛中进行了测试,其中人类裁判扮演UT2004并评估由人或机器人控制的其他化身的人性。 NeuroBot紧随其后,获得36%的人类评价,而人类最多的人达到67%。我们还开发了一种人性度指标,将多个化身行为的统计量合并为一个数。在我们使用该指标的实验中,NeuroBot被评为人类的33%,而人类最多的人达到了73%。

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