An Introduction to Knowledge Engineering

ISBN-13: 9781846284755 / Angielski / Miękka / 2006 / 290 str.

Simon Kendal; Malcolm Creen

Opis

Adopting a 'workbook' style, this book includes methodologies for the development of hybrid information systems, and covers neural networks, case based reasoning and genetic algorithms as well as expert systems. Numerous pointers to web based resources and research are also included.

Recenzje

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)

Spis treści

An Introduction to Knowledge Engineering.- Types of Knowledge-Based Systems.- Knowledge Acquisition.- Knowledge Representation and Reasoning.- Expert System Shells, Environments and Languages.- Life Cycles and Methodologies.- Uncertain Reasoning.- Hybrid Knowledge-Based Systems.

Blurb

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.