Decision-Theoretic Troubleshooting: A Framework for Repair and
  Experiment
  We develop and extend existing decision-theoretic methods for troubleshooting
a nonfunctioning device. Traditionally, diagnosis with Bayesian networks has
focused on belief updating---determining the probabilities of various faults
given current observations. In this paper, we extend this paradigm to include
taking actions. In particular, we consider three classes of actions: (1) we can
make observations regarding the behavior of a device and infer likely faults as
in traditional diagnosis, (2) we can repair a component and then observe the
behavior of the device to infer likely faults, and (3) we can change the
configuration of the device, observe its new behavior, and infer the likelihood
of faults. Analysis of latter two classes of troubleshooting actions requires
incorporating notions of persistence into the belief-network formalism used for
probabilistic inference.
