This paper presents a novel map building approach for path planning purposes, which takes into account the uncertainty inherent in sensor measurements. To this end, Bayesian estimation and Dempster-Shafer evidential theory are used to fuse the sensory information and to update the occupancy and evidential grid maps, respectively. The approach is illustrated using actual measurements from a labo...

By analyzing the relationships among chance, weight of evidence and degree of belief, it is shown that the assertion \chances are special cases of belief functions" and the assertion \Dempster's rule can be used to combine belief functions based on distinct bodies of evidence" together lead to an inconsistency in Dempster-Shafer theory. To solve this problem, some fundamental postulates of the ...

Human resources are an important asset for the company to develop and realize company's goals. One of efforts optimize capacity employees is know their personality. Personality form possessed by individual in behaving all characteristics that distinguish one from another. Knowing personality themselves. Because knowing a person's personality, can maximize potential place certain positions suit ...

Issues of formalisirig and interpreting epistemic uncertainty have always played a prominent role in Artificial Intelligence. The Dempster-Shafer (DS) theory of partial beliefs is one of the most-well known formalisms to address the partial knowledge. Similarly to the DS theory, which is a généralisation of the classical probability theory, fuzzy logie provides an alternative reasoning apparatu...

There are described some algebraic structures on a space of belief functions on a two element frame namely so called Dempster s semigroup with Dempster s operation dempsteroids and their basic properties The present paper is devoted to the investi gation of automorphisms of Dempster s semigroup Full characterization of general and ordered automorphisms is obtained their parametric description i...

This paper describes a novel methodology for predicting fault prone modules. The methodology is based on Dempster-Shafer (D-S) belief networks. Our approach consists of three steps: First, building the Dempster-Shafer network by the induction algorithm; Second, selecting the predictors (attributes) by the logistic procedure; Third, feeding the predictors describing the modules of the current pr...