The Handbook Of Applied Expert Systems

The Handbook of Applied Expert Systems is a landmark work dedicated solely to this rapidly advancing area of study. Edited by Jay Liebowitz, a professor, author, and consultant known around the world for his work in the field, this authoritative source covers the latest expert system technologies, applications, methodologies, and practices. The book features contributions from more than 40 of the world's foremost expert systems authorities in industry, government, and academia. The Handbook is organized into two major sections. The first section explains expert systems technologies while the second section focuses on applied examples in a wide variety of industries. Key topics covered include fuzzy systems, genetic algorithm development, machine learning, knowledge representation, and much more.

As the complexities and problems that plague law enforcement agencies continue to proliferate, the need to utilize every available tool has led to the application of expert systems to law enforcement activities. This first book to explore this application is both practical and conceptually clear as it explains the potential utility of expert systems and their impact on operations and management. Such systems can support command and control through computer-aided dispatching, assist in the solution of high volume crimes such as residential burglaries, aid in the design of programs for the apprehension and prosecution of career criminals and repeat offenders, upgrade personnel through enhanced training programs, and provide an improved method for the delivery of technical assistance and training services. Until now, literature to assist organizations that could benefit from this technology has been scarce. Ratledge and Jacoby have geared their discussions to a wide audience which includes both practitioners and the academic community. This handbook offers clear, systematic explanations of the applications of expert systems in the world of law enforcement. It discusses the impact of these systems on traditional ways of policing and crime solving, and details a set of practical guidelines for jurisdictions considering the use of expert systems. The text is designed to present information in an order that progresses from general to technical aspects of the subject. The first two chapters provide an overview of expert systems as they apply to different law enforcement areas and discuss the policy issues they create. The next section describes practical applications of expert systems in computer-aided dispatching, crime solving, and training. Chapter 4 explains the basic steps in building expert systems, its terminology, and general characteristics. Chapter 5 offers an introduction to artificial intelligence and its uses in problem solving and expert systems. Written with the expert systems designer or data processing manager in mind, Chapter 6 reviews the problems encountered in linking inferencing to data processing and the efficiencies and technical requirements of the system. In Chapter 7, a case study of the Baltimore County Police Department's expert system for residential burglaries is presented and the steps taken in the development of that system are described. Included in the valuable appendices are a list of vendors, two bibliographies including an annotated one relating to current policing issues and one dealing with technical publications, and a glossary. This timely handbook will enable practitioners in criminal justice to make informed decisions regarding the implementation of expert systems. It also provides up-to-the-minute information for computer system consultants and academicians and students in computer science and criminal justice administration.

Building an expert system involves eliciting, analyzing, and interpreting the knowledge that a human expert uses when solving problems. Expe rience has shown that this process of "knowledge acquisition" is both difficult and time consuming and is often a major bottleneck in the production of expert systems. Unfortunately, an adequate theoretical basis for knowledge acquisition has not yet been established. This re quires a classification of knowledge domains and problem-solving tasks and an improved understanding of the relationship between knowledge structures in human and machine. In the meantime, expert system builders need access to information about the techniques currently being employed and their effectiveness in different applications. The aim of this book, therefore, is to draw on the experience of AI scientists, cognitive psychologists, and knowledge engineers in discussing particular acquisition techniques and providing practical advice on their application. Each chapter provides a detailed description of a particular technique or methodology applied within a selected task domain. The relative strengths and weaknesses of the tech nique are summarized at the end of each chapter with some suggested guidelines for its use. We hope that this book will not only serve as a practical handbook for expert system builders, but also be of interest to AI and cognitive scientists who are seeking to develop a theory of knowledge acquisition for expert systems.

Expert systems allow scientists to access, manage, and apply data and specialized knowledge from various disciplines to their own research. Expert Systems in Chemistry Research explains the general scientific basis and computational principles behind expert systems and demonstrates how they can improve the efficiency of scientific workflows

This logical and integrated approach to implementation of expert systems shows how an expert system is conceived and built using commercially available ES Shells. Taking a single coherent example, it follows the implementation team from initial evaluation of a problem through knowledge engineering steps and implementation tricks to the completion of a deliverable system. The book follows the team as they grapple with management problems, design issues, and delivery/validation. Theoretical material is introduced in the order of design problems faced by the team, providing a clear framework for all topics discussed. As the project progresses, increasingly sophisticated techniques are introduced and illustrated in detail.

Cryptography, in particular public-key cryptography, has emerged in the last 20 years as an important discipline that is not only the subject of an enormous amount of research, but provides the foundation for information security in many applications. Standards are emerging to meet the demands for cryptographic protection in most areas of data communications. Public-key cryptographic techniques are now in widespread use, especially in the financial services industry, in the public sector, and by individuals for their personal privacy, such as in electronic mail. This Handbook will serve as a valuable reference for the novice as well as for the expert who needs a wider scope of coverage within the area of cryptography. It is a necessary and timely guide for professionals who practice the art of cryptography. The Handbook of Applied Cryptography provides a treatment that is multifunctional: It serves as an introduction to the more practical aspects of both conventional and public-key cryptography It is a valuable source of the latest techniques and algorithms for the serious practitioner It provides an integrated treatment of the field, while still presenting each major topic as a self-contained unit It provides a mathematical treatment to accompany practical discussions It contains enough abstraction to be a valuable reference for theoreticians while containing enough detail to actually allow implementation of the algorithms discussed Now in its third printing, this is the definitive cryptography reference that the novice as well as experienced developers, designers, researchers, engineers, computer scientists, and mathematicians alike will use.

This book is written for software engineers, software project leaders, and software managers who would like to introduce a new advanced software technology, expert systems, into their product. Expert system technology brings into programming a new dimension in which "rule of thumb" or heuristic expert knowledge is encoded in the program. In contrast to conventional procedural languages {e. g. , Fortran or C}, expert systems employ high-level programming languages {Le. , expert system shells} that enable us to capture the judgmental knowledge of experts such as geologists, doctors, lawyers, bankers, or insurance underwriters. Past expert systems have been more successfully applied in the problem areas of analysis and synthesis where the boundary of lo;nowledge is well defined and where experts are available and can be identified. Early successful applications include diagnosis systems such as MYCIN, geological systems such as PROSPECTOR, or design/configu ration systems such as XC ON. These early expert systems were mainly applicable to scientific and engineering problems, which are not theoreti cally well understood in terms of decisionmaking processes by their experts and which therefore require judgmental assessment. The more recent expert systems are being applied to sophisticated synthesis problems that involve a large number of choices, such as how the elements are to be compared. These problems normally entailed a large search space and slower speed for the expert systems designed. Examples of these systems include factory scheduling applications such as ISIS, or legal reasoning applications such as TAXMAN.