A Hybrid Plan Recognition Model for Alzheimer´s Patients: Interleaved-Erroneous Dilemma

In the context of an intelligent habitat assisting an occupant with Alzheimer´s disease, the goal of plan recognition is to predict the patient´s behavior in order to identify the various ways of supporting him in carrying out his daily activities. However, this situation raises the following dilemma: the observation of a new action, different from the expected one, cannot be directly interpreted as an error; this action can instead constitute the beginning of a second plan, carried out in an interleaved way. In addition, this same action is not inevitably the result of a multiple plan realization; it can effectively be an error. To resolve this dilemma, we propose in this paper a hybrid recognition model based on probabilistic description logic. An implementation of this model was tested in a real smart home infrastructure, by simulating a set of real case scenarios.