This book offers a systematic approach to knowledge engineering problems. It gives a brief overview of knowledge engineering systems and environments, covering both classical and recent techniques of the design and evaluation of them. Detailed descriptions of particular techniques and applications are also provided.

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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

The successful implementation of CASE technology requires a long-term and comprehensive commitment to the pursuit of raising the quality of software design and ultimately improving the information management within the organization. Computer-Aided Software Engineering: Issues and Trends for the 1990s and Beyond covers all aspects of preparing an organization for the successful implementation of a CASE program. Actual case studies, empirical research and theoretical suppositions are used to assess how CASE is being used today and to predict future directions.

In the last few years rapid advances have been made in reproductive medicine, making it necessary for those involved to regularly update their knowledge. The purpose of this book is to describe the state of the art in this field, making it possible for the reader to gain an orientation among all the diagnostic and therapeutic potentials of modern reproductive medicine in order to advise patients fully. Chapters from the fields of gynecology, and reproductive medicine in a specific sense provide knowledge about these subjects. Authors of international standing have contributed chapters on their specialties. These chapters together form a book describing the state of the art in the diagnosis and therapy of sterility in gynecology and andrology.

In the past half century, we have experienced two major waves of methodological development in the study of human behavior in space and time. The fIrst wave was the well known "quantitative revolution" which propelled geography from a mainly descriptive discipline to a scientifIc discipline using formalism such as probability, statistics, and a large-number of mathematical methods for analyzing spatial structures and processes under certainty and uncertainty. The second wave is the recent advancement of geographical information systems which equips geographers with automation in the storage, retrieval, analysis, and display of data. Both developments have significant impacts on geographical studies in general and solutions to real life spatio-temporal problems in particular. They have found applications in urban and regional planning, automated mapping and facilities management, transportation planning and management, as well as environmental planning and management, to name but a few examples. Both developments have one thing in common. They one way or the other use computer to process and analyze data. However, not until recently, there has been very little interaction between the two. Quantitative models have largely been developed independent of the underlying data models and structures representing the spatial phenomena or processes under study. Display of analysis results has been primitive in terms of the utilization of computer graphic technologies. Formal models, in addition to their technical difficulties, have poor capability in communication with users. Geographical information systems, on the other hand, have originally been developed with a slight intention to entertain powerful analytical models.

This volume contains the revised versions of the papers presented at the Eighth International Symposium on Methodologies for Intelligent Systems (ISMIS '94), held in Charlotte, North Carolina, USA in October 1994. Besides four invited contributions by renowned researchers on key topics, there are 56 full papers carefully selected from more than 120 submissions. The book presents the state of the art for methodologies for intelligent systems; the papers are organized in sections on approximate reasoning, evolutionary computation, intelligent information systems, knowledge representation, methodologies, learning and adaptive systems, and logic for AI.

Shell Process Control Workshop covers the proceedings of a workshop of the same name, held in Houston, Texas on December 15, 1986. The said workshop seeks to improve the communication process between academic researchers, industrial researchers, and the engineering community in the field of process control, and in turn improve understanding of the nature of the control problems. The book covers topics such as design methodology based on the fundamental control; expert systems in process control and optimization; artificial intelligence; and adaptive control for processes. Also covered are topics such the approach of systems engineering to process modeling; modeling and control of dispersed phase systems; and advances in the use of the internal model control. The text is recommended for researchers and practitioners in the field of engineers who would like to know more about process control and modeling.