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FP5

REVIGIS Résumé de rapport

Project ID: IST-1999-14189
Financé au titre de: FP5-IST
Pays: France

Belief revision and binary decision tree

Binary Decision Diagrams (BDD) is a compact and empirically efficient data structure for representing formulae in propositional logic. More precisely, BDDs allow a compact representation of the models of a formula. In the framework of the flooding application, we explored two possible uses of BDDs to achieve revision.

The first approach, considering a K*A revision operation, we tried to encode all the knowledge of K and A into a single BDD, and then select suitable models of the revised knowledge. This approach appears to be intractable because of the huge data size.

We recently developed a new approach, which uses BDD. This approach relies on a semantic characterization of our revision operation, which leads to the building of three separate BDDs: one for the knowledge in K, one for the knowledge in A a third BDD containing the preference ordering on the knowledge which defines the revision strategy.

This new approach has better partial results of complexity than the first one. The theoretical model has been fully described, and now we start an experimental phase. This is a mandatory step when dealing with BDDs, as if the worst-case complexity is still high, the mean case is too difficult to express theoretically, thus requiring experimentation.

Contact

Eric WURBEL, (assistant professor)
Tél.: +49-414-2887
Fax: +49-414-2897
E-mail