Our approach generates troubleshooting plans in the face of uncertainty in the relationships among components and device status, observations, as well as the affect of actions on device status. Included in our approach is a Bayesian-network representation of these relationships. We have applied our technique successfully to troubleshooting problems with printing, photocopier feeders, automobiles, and gas turbines. We report empirical findings demonstrating the high quality of plans produced by our approach.
Recent work emphasizes a cost benefit analysis rather than probability bounds.
Similarly Heckerman et al. Troubleshooting under uncertainty. The graph only includes citing articles where the year of publication is known.