The Dempster Shafer theory of evidence concerns the elicitation and manipulationof degrees of belief rendered by multiple sources of evidence to a commonset of propositions. Information indexing and retrieval applications use a varietyof quantitative means - both probabilistic and...

In developing methods for dealing with uncertainty in reasoning systems, itis important to consider the needs of the target applications. In particular,when the source of inferential uncertainty can be tracked to distributions ofexpert opinions, there might be different ways to model the...

We consider a situation in which multiple decision-makers who are partitionedinto two or more distinct groups are asked to recommend a uniform course ofaction which is drawn from a finite and explicit set of potential alternatives.We present group-level and player-level mechanisms to reach a...

Belief updating schemes in artificial intelligence may be viewed as threedimensional languages, consisting of a syntax (e.g. probabilities or certaintyfactors), a calculus (e.g. Bayesian or CF combination rules), and a semantics(i.e. cognitive interpretations of competing formalisms). This paper...

Uncertain facts and inexact rules can be represented andprocessed in standard Prolog through meta-interpretation. Thisrequires the specification of appropriate parsers and beliefcalculi. We present a meta-interpreter that takes a rule-basedbelief calculus as an external variable. The...

Most research on rule-based inference under uncertainty hasfocused on the normative validity and efficiency of variousbelief-update algorithms. In this paper we shift the attentionto the inputs of these algorithms, namely, to the degrees ofbeliefs elicited from domain experts. Classical methods...

We present a model for representing relevance and classification decisions ofmultiple catalogers in the context of a hierarchical bibliographical database.The model is based on the Dempster-Shafer theory of evidence. Conceptslike ambiguous relevance, inexact classification, and pooled...

One of the key challenges in designing expert systems is a credible representationof uncertainty and partial belief. During the past decade, a number ofrule-based belief languages were proposed and implemented in applied systems.Due to their quasi-probabilistic nature, the external validity of...

Several researchers characterized the activation functions under which multilayer feedforwardnetworks can act as universal approximators. We show that all the characterizationsthat were reported thus far in the literature ark special cases of the following general result:a standard multilayer...

The problem of modeling uncertainty and inexact reasoning inrule-based expert systems is challenging on nonnative as well oncognitive grounds. First, the modular structure of the rule-basedarchitecture does not lend itself to standard Bayesianinference techniques. Second, there is no consensus...