Table of Contents

An Introduction to Knowledge Engineering.- Data, Information and Knowledge.- Skills of a Knowledge Engineer.- An Introduction to Knowledge Based Systems.- Types of Knowledge Based System-Expert Systems.- Neural Networks.- Case Based Reasoning.-Genetic Algorithms.- Intelligent Agents.- Data Mining-Knowledge Acquisition.- Knowledge Representation and Reasoning.- Using Knowledge.- Logic, Rules and Representation.- Developing Rule Based Systems.- Semantic Networks.- Frames.- Expert System Shells, Environments and Languages 169.- Expert System Shells.- Expert System Development Environments.- Use of AI Languages.- Lifecycles and Methodologies.- The Need for Methodologies.- Blackboard Architectures.- Problem Solving Methods.- KADS-HyM (the Hybrid Methodology).- Building a well Structured Application Using Aion BRE.- Uncertain Reasoning.- Hybrid Knowledge.- Based Systems.- Index.

Reviews

From the reviews: "The book is written in a modern style, which should encourage undergraduate students to read it. … Overall, the book covers all classical topics of knowledge-based systems: knowledge acquisition, representation, expert system shells, and life cycles. It could make a good textbook for undergraduate courses … and the students research the uniform resource locator (URL) links provided." (Aladdin Ayesh, ACM Computing Reviews, Vol. 49 (4), April, 2008)