Computer Science – Artificial Intelligence
Scientific paper
2007-09-04
Proceedings of Fusion 2007 International Conference, Quebec City, Canada, July 2007
Computer Science
Artificial Intelligence
13 pages. Presented at Fusion 2007 International Conference, Quebec City, Canada, July 2007
Scientific paper
In this paper we extend the new family of (quantitative) Belief Conditioning Rules (BCR) recently developed in the Dezert-Smarandache Theory (DSmT) to their qualitative counterpart for belief revision. Since the revision of quantitative as well as qualitative belief assignment given the occurrence of a new event (the conditioning constraint) can be done in many possible ways, we present here only what we consider as the most appealing Qualitative Belief Conditioning Rules (QBCR) which allow to revise the belief directly with words and linguistic labels and thus avoids the introduction of ad-hoc translations of quantitative beliefs into quantitative ones for solving the problem.
Dezert Jean
Smarandache Florentin
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