Computer Science – Artificial Intelligence
Scientific paper
2006-06-14
Computer Science
Artificial Intelligence
Scientific paper
The problem of combining 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 combination have been proposed in the literature. The consensus operator for combining beliefs has nice properties and produces more intuitive results than Dempster's rule, but has the limitation that it can only be applied to belief distribution functions on binary state spaces. In this paper we present a generalisation of the consensus operator that can be applied to Dirichlet belief functions on state spaces of arbitrary size. This rule, called the cumulative rule of belief combination, can be derived from classical statistical theory, and corresponds well with human intuition.
No associations
LandOfFree
The Cumulative Rule for Belief Fusion does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with The Cumulative Rule for Belief Fusion, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The Cumulative Rule for Belief Fusion will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-196937