Affiliations: University of Rostock, Institute of Computer Science, Mobile Multimedia Information Systems Group, Albert-Einstein-Straße 22, D-18059 Rostock, Germany. E-mail: [email protected]
Abstract: 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.
Keywords: Assistive software, smart environments, model based engineering, human behavior modeling
