Expert Systems

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FUNDAMENTALS OF EXPERT SYSTEMS

This chapter introduces the basic concepts of expert systems. The hierarchical process of developing expert systems is presented, as well as the essential characteristics of expert systems are presented. More specific details of the concepts introduced in this chapter are covered in subsequent chapters. 2.1 EXPERT SYSTEMS PROCESS

This book is organized inthe structure of a strategic process for developing successful expert systems. Figure 2.1 presents the hierarchy of topics as they are presented here and in the subsequent chapters. The strategic process is recommended for anyone venturing into the technology of expert systems from the standpoint of training, research, or applications. This chapter covers the basic concepts of expert systemstechnology. A basic understanding of these concepts is essential to getting the most out of expert systems. More specific details of the concepts presented in this chapter are discussed in appropriate sections of the subsequent chapters. Chapter 3 covers problem analysis. To be effective, the right problems must be selected for expert systems implementation. The principle of ‘‘garbage in, garbage out’’is also applicable here. Wrong problems lead to incorrect implementation of expert systems. Chapter 4 covers knowledge engineering. Knowledge acquisition is a critical aspect of the expert systems effort. If the knowledge collected is garbage, the best that can be expected from a system is garbage. Chapter 5 presents probabilistic and fuzzy reasoning. Chapter 6 presents fuzzy systems techniquesfor handling uncertainty in expert systems. Chapter 7 presents neural networks. Chapter 8 covers neural-fuzzy networks. Chapter 9 presents the technique of evolutionary computing. Chapter 10 presents an application to manufacturing. Chapter 11 presents an application to forecasting.
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FUNDAMENTALS OF EXPERT SYSTEMS

MAINTENANCE IMPLEMENTATION, INTEGRATION TESTING, VERIFICATION,VALIDATION DEVELOPMENT PROCESS TOOL SELECTION Tasks KNOWLEDGE REPRESENTATION KNOWLEDGE ACQUISITION PROBLEM SELECTION CONCEPTS BACKGROUND

Time

Figure 2.1. Hierarchy of expert systems development process.

2.2

EXPERT SYSTEMS CHARACTERISTICS

By definition, an expert system is a computer program that simulates the thought process of a human expert to solve complex decision problems in aspecific domain. This chapter addresses the characteristics of expert systems that make them different from conventional programming and traditional decision support tools. The growth of expert systems is expected to continue for several years. With the continuing growth, many new and exciting applications will emerge. An expert system operates as an interactive system that responds to questions, asksfor clarification, makes recommendations, and generally aids the decision-making process. Expert systems provide expert advice and guidance in a wide variety of activities, from computer diagnosis to delicate medical surgery. Various definitions of expert systems have been offered by several authors. A general definition that is representative of the intended functions of expert systems is:
Anexpert system is an interactive computer-based decision tool that uses both facts and heuristics to solve difficult decision problems based on knowledge acquired from an expert.

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EXPERT SYSTEMS CHARACTERISTICS

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An expert system may be viewed as a computer simulation of a human expert. Expert systems are an emerging technology with many areas for potential applications. Pastapplications range from MYCIN, used in the medical field to diagnose infectious blood diseases, to XCON, used to configure computer systems. These expert systems have proven to be quite successful. Most applications of expert systems will fall into one of the following categories:
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Interpreting and identifying Predicting Diagnosing Designing Planning Monitoring Debugging and testing...