Abstract: As intelligence in smart homes increasingly get sophisticated, it has become necessary adopting ontological reasoning in these domains. However, ontologies presently lack a standardised representation for uncertainty in knowledge. A key challenge therefore lies in developing ontology-based decision-making models that can integrate domain uncertainty. In this paper, a decision network extension to OWL ontology using only a subset of domain concepts relevant for probabilistic modelling is proposed. This relevant set of concepts in ontology can be generated on the fly using an algorithm, OWLMB, introduced in this paper. Given an ontology and a class as inputs to OWLMB, Markov boundary of the class is returned as this minimum relevant set. Also, representations for decision and utility nodes are proposed as an extension of valid decision situation to ontology. Validation of this approach in a smart home scenario shows its feasibility in a real application domain.
Keywords: Smart home, ontology, uncertainty reasoning, knowledge representation, semantic web