Possible conflicts, ARRs, and conflicts

Consistency-based diagnosis is the most widely used approach to model-based diagnosis within the Artificial Intelligence community. It is usually carried out through an iterative cycle of behavior prediction, conflict detection, and candidate generation and refinement. Many approaches to consistency-based diagnosis have relied on some kind of on-line dependency-recording mechanism for conflict calculation. These techniques have had different problems, specially when applied to dynamic systems. Recently, off-line compilation of dependencies has been established as a suitable alternative approach. In this work we compare one compilation technique, based on the possible conflict concept, with results obtained with the classical on-line dependency recording engine as in GDE. Moreover, we compare possible conflicts with another compilation technique coming from the FDI community, which is based on analytical redundancy relations. Finally, we study the relationship between possible conflicts, analytical redundancy relations, and conflicts.