In this paper, one studies the famous well-known and challenging Tweety Penguin Triangle Problem (TPTP or TP2) pointed out by Judea Pearl in one of his books. We first present the solution of the TP2 based on the fallacious Bayesian reasoning and prove that reasoning cannot be used to conclude on the ability of the penguin-bird Tweety to fly or not to fly. Then we present in details the counter...

The method of reasoning with uncertain information known as Dempster-Shafer theory arose from the reinterpretation and development of work of Arthur Dempster [Dempster, 67; 68] by Glenn Shafer in his book a mathematical theory of evidence [Shafer, 76], and further publications e.g., [Shafer, 81; 90]. More recent variants of Dempster-Shafer theory include the Transferable Belief Model see e.g., ...

A method of diagnosis support allowing analogous consideration of fuzzy, scaled and precise medical parameters in reasoning is proposed in the paper. The method is based on Dempster-Shafer theory of evidence and makes it possible to represent conformity of patient’s findings with symptoms in diagnostic rules. Theoretical discussion is illustrated by an example.

A system capable of performing approximate inferences under time constraints is presented. Censored production rules are used to represent both domain and control information. These are given a probabilistic semantics and reasoning is performed using a scheme based on Dempster-Shafer theory. Examples show the naturalness of the representation and the flexibility of the system. Suggestions for f...

We propose to use evidential reasoning in order to relax Bayesian decisions given by a Markovian classification algorithm (ICM). The Dempster–Shafer rule of combination enables us to fuse decisions in a local spatial neighborhood which we further extend to be multisource. This approach enables us to more directly fuse information. Application to the classification of very noisy images produces ...

Incidence Calculus and Dempster-Shafer Theory of Evidence are both theories to describe agents' de­ grees of belief in propositions, thus being appropri­ ate to represent uncertainty in reasoning systems. This paper presents a straightforward equivalence proof between some special cases of these theories.

We introduce a general theory of epistemic random fuzzy sets for reasoning with or crisp evidence. This framework generalizes both the Dempster-Shafer belief functions, and possibility theory. Independent are combined by generalized product-intersection rule, which extends Dempster's rule combining product conjunctive combination distributions. Gaussian numbers their multi-dimensional extension...

This paper addresses reasoning under uncertainty for knowledge-based fault diagnosis. We illustrate how the fault diagnosis task is influenced by uncertainty. Furthermore, we compare how the diagnosis task is solved in the Bayesian and the Dempster-Shafer reasoning framework, in terms of both diagnostic performance and additional objectives, like transparency, adaptability, and computational ef...