A model for CBR systems that adapt to rapidly changing context

Challenges in context-sensitive applications are not limited to reasoning. Rapid changes in the environment, which are reflected by the context information, pose a particular challenge. During the run of a single CBR cycle, a lazy adaptation can be used to deal with this challenge of rapidly changing context. In an ambient intelligence system, there is also the need to modularize the knowledge according to the overall system. We present a model for CBR in such a setting. The model consists of an extended/modified CBR process, a knowledge model, and an architecture pattern for embedding a CBR module into an ambient intelligence system. Our focus is on the context-aware adaptation of the actions to be executed when a certain situation is recognized. The technical feasibility of our model has been evaluated with an application in the area of ambient assisted living for elderly people.