Knowledge representation issues in default reasoning

Knowledge Representation and Reasoning

IEEE INTELLIGENT SYSTEMS Except perhaps for the AI naysayers, AI practitioners are creators—of software artifacts, their underlying algorithms, and their underlying theories. We begin our feature with Herbert Simon, one of our three contributors (together with John McCarthy and Oliver Selfridge) who are our links to the landmark Dartmouth conference in 1956, where modern AI is often said to hav...

Knowledge Representation and Reasoning

McIlraith & Allin, CSC384, University of Toronto, Winter 2018 Knowledge Representation (KR) • This material is covered in chapters 7– 9 and 12 (R&N, 3rd ed) (chapters 7—10 (R&N, 2nd ed) ). • Chapter 7 provides useful motivation for logic, and an introduction to some basic ideas. It also introduces propositional logic, which is a good background for first-order logic. • What we cover here is mai...

On Knowledge Representation issues

Knowledge Representations issues take on special significance in the light of development of the novel Web’s reality that involves the Semantic Web, GRID, P2P and other today’s ITs. In contrast to the previous IT evolution’s stages, the recent one utilizes ontology as separated resource. An elaborate knowledge representation approach implies an efficiency of knowledge-based systems and their in...

Knowledge Representation Issues in Control Knowledge Learning

Configuration Knowledge Representation and Reasoning

Configuration models specify the set of possible configurations (solutions). A configuration model togetherwith a defined set of (customer) requirements are themajor elements of a configuration task (problem). In this chapter, we discuss different knowledge representations that can be used for the definition of a configuration model. We provide examples that help to further develop the understa...