Abstract
Failure diagnosis in large and complex systems is a critical and challenging task. In the realm of model based diagnosis on discrete event systems, computing a failure diagnosis means computing the set of system behaviours that could explain observations. Depending on the diagnosed system, such behaviours can be numerous, so that a problem of representing them is induced. The paper discusses about this problem and presents a way of representing a diagnosis by the use of a partial order reduction technique.
| Original language | English |
|---|---|
| Pages (from-to) | 208-212 |
| Number of pages | 5 |
| Journal | Proceedings of the International Conference on Tools with Artificial Intelligence |
| Publication status | Published - 2003 |
| Event | Proceedings: 15th IEEE International Conference on Tools with artificial Intelligence - Sacramento, CA, United States Duration: 3 Nov 2003 → 5 Nov 2003 |
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