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An Introduction to Knowledge Engineering de Simon Kendal

An Introduction to Knowledge Engineering

Autor Simon Kendal, Malcolm Creen
en Limba Engleză Paperback – 4 oct 2006
An Introduction to Knowledge Engineering presents a simple but detailed exp- ration of current and established work in the ?eld of knowledge-based systems and related technologies. Its treatment of the increasing variety of such systems is designed to provide the reader with a substantial grounding in such techno- gies as expert systems, neural networks, genetic algorithms, case-based reasoning systems, data mining, intelligent agents and the associated techniques and meth- ologies. The material is reinforced by the inclusion of numerous activities that provide opportunities for the reader to engage in their own research and re?ection as they progress through the book. In addition, self-assessment questions allow the student to check their own understanding of the concepts covered. The book will be suitable for both undergraduate and postgraduate students in computing science and related disciplines such as knowledge engineering, arti?cial intelligence, intelligent systems, cognitive neuroscience, robotics and cybernetics. vii Contents Foreword vii 1 An Introduction to Knowledge Engineering. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Section 1: Data, Information and Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Section 2: Skills of a Knowledge Engineer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Section 3: An Introduction to Knowledge-Based Systems. . . . . . . . . . . . . . . . . 18 2 Types of Knowledge-Based Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 Section 1: Expert Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Section 2: Neural Networks. . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 Section 3: Case-Based Reasoning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 Section 4: Genetic Algorithms. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Section 5: Intelligent Agents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Section 6: Data Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 3 Knowledge Acquisition. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 4 Knowledge Representation and Reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 Section 1: Using Knowledge. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Section 2: Logic, Rules and Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116 Section 3: Developing Rule-Based Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Section 4: Semantic Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Specificații

ISBN-13: 9781846284755
ISBN-10: 1846284759
Pagini: 300
Ilustrații: X, 290 p. 33 illus.
Dimensiuni: 155 x 235 x 16 mm
Greutate: 0.42 kg
Ediția:2007
Editura: SPRINGER LONDON
Colecția Springer
Locul publicării:London, United Kingdom

Public țintă

Lower undergraduate

Cuprins

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.

Recenzii

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)

Textul de pe ultima copertă

Knowledge Engineering, as a discipline and a profession, has emerged from the practical application of decades of research into artificial intelligence and intelligent systems. In particular, knowledge engineering refers to the development of systems that use knowledge, rather than data, to solve many novel computing problems. This is achieved by the application of computing techniques, closely associated with human cognitive processes, for transforming data into knowledge.
An Introduction to Knowledge Engineering presents a simple but detailed exploration of current and established work in the field. Its simple yet comprehensive treatment of knowledge based systems will provide the reader with a substantial grounding in such technologies as:
•expert systems
•neural networks
•genetic algorithms
•case based reasoning systems
•data mining
•intelligent agents.
The text includes activities and self assessments that provide opportunities for the reader to reflect on and reinforce their understanding of the concepts as they progress.
The book will be suitable for both undergraduate and postgraduate students in computing science and related disciplines such as Knowledge Engineering, Artificial Intelligence, Intelligent systems, Cognitive Neuroscience, Robotics and Cybernetics.
In addition, it is expected that anyone interested or involved in sophisticated information system developments will find the book a valuable source of ideas and guidance.

Caracteristici

Takes an innovative workbook approach to explore current and established work in knowledge engineering