Action selection in interactive model-based diagnosis

Abstract

The authors developed a probabilistic diagnosis theory that incorporates probabilistic reasoning into model-based diagnosis. In addition to the structural and functional information normally used in model-based diagnosis, probabilities of component failure are also used to solve the two major subtasks of interactive model-based diagnosis: hypothesis generation and action selection. The authors describe the action selection strategy based on this probabilistic theory. The major contributions are the incorporation of probabilistic reasoning into model-based diagnosis and the integration of repair as a part of diagnosis.<>