In Dempster-Shafer (DS) theory, multiple information from the distinct information sources are combined to obtain a single Basic Probability Assignment (BPA) function. The well-known combination rule of Dempster-Shafer (DS) provides the weaker solution to the management of conflicting information at the normalization stage. Even this rule fails and provide the counter intuitive results while co...

In this pa�, we suggest marry ing Dempster-Shafer (DS) theory w1th Knowledge Representation (KR). Born out of this marr iage is the defmition of "Dempster-Shafer Belief Bases", abstract data types representing uncertain knowledge that use DS theory for representing strength of belief about our knowledge, and the linguistic structures of an arbitrary KR system for representing the knowledge itse...

As a generalization of Dempster-Shafer theory, the theory of D numbers is a new theoretical framework for uncertainty reasoning. Measuring the uncertainty of knowledge or information represented by D numbers is an unsolved issue in that theory. In this paper, inspired by distance based uncertainty measures for Dempster-Shafer theory, a total uncertainty measure for a D number is proposed based ...

In this paper, a novel justification of the disjunctive combination rule for multiple independent sources of information based on the redefined combination-mapping rule of multiple multi-valued mappings in the product space of multiple independent sources of information is being proposed. The combination rule reveals a type of logical inference in the human judgment, that is, the OR rule. It ov...

This paper is one of many attempts to introduce graphical Markov models within Dempster-Shafer theory of evidence. Here we take full advantage of the notion of factorization, which in probability theory (almost) coincides with the notion of conditional independence. In Dempster-Shafer theory this notion can be quite easily introduced with the help of the operator of composition. Nevertheless, t...

Multi-classifier combination based on Dempster-Shafer theory of evidence has demonstrated it’s superior performance. In the approach based on Dempster-Shafer theory, the basic probability assignments for evidence are usually derived from classifiers’ global performance. However, our study discovered that while using classifiers’ global performance as basic probability assignments doesn’t necess...

This paper introduces the idea of using the Dempster-Shafer theory of evidence with qualitative values. Dempster-Shafer theory is a formalism for reasoning under uncertainty which may be viewed as a generalisation of probability theory with special advantages in its treatment of ambiguous data and the ignorance arising from it. Here we are interested in applying the theory when the numbers that...