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Towards creating assistive software by employing human behavior models

机译:通过运用人类行为模型来创建辅助软件

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Assistive software becomes more and more important part of our everyday life. As it is not straightforward to create such a system, the engineering of assistive systems is a topic of current research with different applications in healthcare, education and industry. In this paper we introduce three contributions to this field of research. Whereas most assistive systems use approaches for intention recognition based on training data applicable to specific environments and applications, we introduce a training-free approach. We do that by showing that it is possible to generate probabilistic inference systems from causal models for human behavior. Additionally, we collect a list of requirements for context aware assistive software and human behavior modeling for intention recognition and showed that our system satisfies them. We then introduce a software architecture for assistive systems that provides support for this kind of modeling. In addition to introducing the modeling approach and the architecture we show in an experimental way that our approach is suited for smart environments. The collected list of requirements could help a software engineer create a robust and easily adaptable to changes in the environment assistive software.
机译:辅助软件已成为我们日常生活中越来越重要的部分。由于创建这样的系统并非易事,因此辅助系统的工程设计是当前研究的主题,在医疗保健,教育和工业领域具有不同的应用。在本文中,我们介绍了对这一研究领域的三点贡献。大多数辅助系统使用基于适用于特定环境和应用程序的训练数据进行意图识别的方法,但我们引入了免训练方法。通过证明有可能从人类行为的因果模型中生成概率推理系统,可以做到这一点。此外,我们收集了用于上下文识别的辅助软件和用于意图识别的人类行为建模的要求列表,并表明我们的系统满足了这些要求。然后,我们介绍用于辅助系统的软件体系结构,该体系结构为这种建模提供支持。除了介绍建模方法和体系结构之外,我们还以实验方式表明我们的方法适用于智能环境。收集的需求清单可以帮助软件工程师创建健壮且易于适应环境辅助软件的更改。

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