A central design issue in ambient assisted living consists in creating environments which show a smart behavior that is transparent to the user in the sense that the effects of ambient intelligence are easily predictable. Another aspect of behavioral transparency is related to the effective and efficient communication with the user about relevant background knowledge. Rule-based specifications are widely used in today's home automation systems as a means to communicate user knowledge.

This chapter addresses ambient intelligence based on the recognition of the user's intentions to act and discusses approaches that identify user intentions in the context of specific background knowledge about possible tasks and the spatial environment. We give a survey on knowledge-based methods for intention recognition and compare different rule-based formalisms with regard to the trade-off between expressiveness and complexity. Special emphasis is laid on approaches that assume a user moving in an environment which is spatially structured by a partonomy as most indoor and near outdoor environments are.