G. Trafton, Laura M. Hiatt, Anthony M. Harrison, Frank Tanborello, S. Khemlani, A. Schultz
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引用次数: 126
Abstract
We present ACT-R/E (Adaptive Character of Thought-Rational / Embodied), a cognitive architecture for human-robot interaction. Our reason for using ACT-R/E is two-fold. First, ACT-R/E enables researchers to build good embodied models of people to understand how and why people think the way they do. Then, we leverage that knowledge of people by using it to predict what a person will do in different situations; e.g., that a person may forget something and may need to be reminded or that a person cannot see everything the robot sees. We also discuss methods of how to evaluate a cognitive architecture and show numerous empirically validated examples of ACT-R/E models.
我们提出了一种人机交互的认知架构——ACT-R/E (Adaptive Character of Thought-Rational / Embodied)。我们使用ACT-R/E的原因有两个。首先，ACT-R/E使研究人员能够建立良好的人的具体化模型，以了解人们如何以及为什么这样思考。然后，我们利用对人的了解来预测一个人在不同情况下会做什么;例如，一个人可能会忘记一些东西，可能需要被提醒，或者一个人不能看到机器人看到的一切。我们还讨论了如何评估认知架构的方法，并展示了许多经验验证的ACT-R/E模型示例。
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