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. This book is organized in the 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 systems technology. 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 techniques for 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.