Learning Activity Models for Multiple Agents in a Smart Space

Abstract

This paper briefly outlines the scientific area that addresses Ambient In-telligence applications in which not only sensor data, but also knowledge from the human-directed sciences such as biomedical science, neuroscience, and psycho-logical and social sciences is incorporated. This knowledge enables the environ-ment to perform more in-depth, human-like analyses of the functioning of the 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: reflective cou-pled human-environment systems. Finally, further perspectives are discussed for Ambient Intelligence applications based on these reflective coupled human-environment systems.