On the Dempster-Shafer framework and new combination rules
Information Sciences: an International Journal
The Combination of Evidence in the Transferable Belief Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Combining belief functions when evidence conflicts
Decision Support Systems
A logic for uncertain probabilities
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
The consensus operator for combining beliefs
Artificial Intelligence
Probabilistic logic under uncertainty
CATS '07 Proceedings of the thirteenth Australasian symposium on Theory of computing - Volume 65
Exploring different types of trust propagation
iTrust'06 Proceedings of the 4th international conference on Trust Management
A subjective logic formalisation of the principle of polyrepresentation for information needs
Proceedings of the third symposium on Information interaction in context
Dempster's Rule As Seen By Little Colored Balls
Computational Intelligence
How to preserve the conflict as an alarm in the combination of belief functions?
Decision Support Systems
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The problem of fusing beliefs in the Dempster-Shafer belief theory has attracted considerable attention over the last two decades. The classical Dempster's rule has often been criticised, and many alternative rules for belief fusion have been proposed in the literature. We show that it is crucial to consider the nature of the situation to be modelled and to select the appropriate fusion operator as a function thereof. In this paper, we present the cumulative rule and the averaging rule of belief fusion, which represent generalisations of the subjective logic consensus operator for independent and dependent opinions respectively. The generalised operators are applicable to the combination of general basic belief assignments (bbas). These rules, which can be directly derived from classical statistical theory, produce results that correspond well with human intuition.