Abstract
This chapter briefly outlines how dynamic computational models, and in particular temporal-causal network models, can contribute to smarter applications. The scientific area that addresses Ambient Intelligence (also called Pervasive Computing) applications is discussed in which both sensor data and knowledge from the human-directed sciences such as health sciences, neurosciences, and psychological and social sciences are incorporated. This knowledge enables the environment to perform more in-depth, human-like analyses of the functioning of observed humans, and to come up with better informed actions. It is discussed which ingredients are important to realise this view, and how frameworks can be developed to combine them to obtain the intended type of systems: coupled reflective human-environment systems. Such systems include computational models by which they are able to model and simulate (parts of) their own behavior. Finally, further perspectives are discussed for Ambient Intelligence applications based on these coupled reflective systems.
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Treur, J. (2016). Making Smart Applications Smarter. In: Network-Oriented Modeling. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-45213-5_16
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DOI: https://doi.org/10.1007/978-3-319-45213-5_16
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