A connectionist model for robust reasoning, CONSYDERR, is proposed to account for some common reasoning patterns found in commonsense reasoning and to remedy the brittleness problem. A dual representational scheme is devised, which utilizes both localist representation and distributed representation with features. We explore the synergy resulted from the interaction between these two types of r...

Multi-relational networks are used extensively to structure knowledge. Perhaps the most popular instance, due to the widespread adoption of the Semantic Web, is the Resource Description Framework (RDF). One of the primary purposes of a knowledge network is to reason; that is, to alter the topology of the network according to an algorithm that uses the existing topological structure as its input...

The material in this document is covered by the provisions of the Copyright Act, by Canadian laws, policies, regulations and international agreements. Such provisions serve to identify the information source and, in specific instances, to prohibit reproduction of materials without written permission. For more information visit Les renseignements dans ce document sont protégés par la Loi sur le ...

Water scarcity is a global issue confronting the present generation, particularly acute in arid regions such as Palestine. Treated wastewater reuse recognized strategic solution. The challenge obtaining effluent quality that meets requirements of area how to select best treatment technology. A multi-criteria decision-making method necessary for assessing sustainability different technologies. T...

We demonstrate how evidential reasoning can be applied in the domain of graphical user interfaces to provide the reliability and robustness of input interpretation expected by users of companion systems. For this purpose an existing approach using the transferable belief model from the robotic domain is adapted and extended.

We introduce a justification logic with a novel constructor for evidence terms, according to which the new information itself serves as evidence for believing it. We provide a sound and complete axiomatization for belief expansion and minimal change and explain how the minimality can be graded according to the strength of reasoning. We also provide an evidential analog of the Ramsey axiom.

In this paper, we propose a computational data structure based on the binary join tree where the independence relations of the original directed evidential networks (DEVN) are maintained. The proposed solution uses disjunctive rule of combination (DRC) and generalized Bayesian theorem (GBT), which make possible the use of the conditional belief functions directly for reasoning in the DEVN.