A valuation-based system approach to knowledge representation has shown its advantages in improving computational efficiency and in allowing many decision models including belief networks. This study applies the Dempster–Shafer theory of belief functions and extends its framework to allow coarse valuations, which admit incomplete specification of probabilities and utilities and, therefore, are ...

In many applications, data are often imperfect, incomplete or more generally uncertain. This imperfection has to be integrated into the learning process as an information in itself. The E2M decision trees is a methodology that provides predictions from uncertain data modelled by belief functions. In this paper, the problem of rubber quality prediction is presented with a belief function modelli...

The Dempster-Shafer (D-S) theory of evidence provides a convenient framework for modeling uncertainty in situations where the available evidence is limited or weak. Such situations typically arise in supervised pattern recognition when the training set is small or does not contain samples from all classes. In D-S theory, someone's feeling of uncertainty concerning a certain set of hypotheses is...

A temporal logic of belief and actions (TLBA) is considered. The TLBA allows us to express informational and dynamic properties of computational agents. The considered fragment of TLBA allows one: (1) to present a deduction-based structured decision procedure; (2) to separate a decision procedure for so-called induction-free formulas and (3) to use only logical axioms for such formulas. The mai...

David Lewis [1988, 1996] canvases an anti-Humean thesis about mental states: that the rational agent desires something to the extent that he or she believes it to be good. Lewis offers and refutes a decision-theoretic formulation of it, the ‘Desire-as-Belief Thesis’. Other authors have since added further negative results in the spirit of Lewis’. We explore ways of being antiHumean that evade a...

This work aims to recognize signs which have both manual and nonmanual components by providing a sequential belief-based fusion mechanism. We propose a methodology based on belief functions for fusing extracted manual and non-manual information in a sequential two-step approach. The belief functions based on the likelihoods of the HMMs are used to decide whether there is an uncertainty in the d...

Major Changes to the Second Edition Chapters have been reorganized for improved understanding of the academic plan model on which the book is based. Greater emphasis is placed on the sociocultural contexts that influence curriculum planning. Includes a new chapter on institutional influences that affect curricular decision-making. Two coordinated chapters on learning and selecting instructional...

Research is an inquiry process that has clearly defined parameters and has as its aim the discovery or creation of knowledge, or theory building; testing, confirmation, revision, refutation of knowledge and theory; and/or investigation of problem for local decision making (Hernon, 1991). Leedy and Ormrod (2001) put it as “the systematic process of collecting and analyzing information (data) in ...

Belief revision is a well-research topic within AI. We argue that the new model of distributed belief revision as discussed here is suitable for general modelling of judicial decision making, along with extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment wi...