A Brief Introduction and History
James K. Peckol · 2021
Understanding the concepts of learning and reasoning is playing an increasingly significant role in the modern high-tech design, development, and implementation of perceptrons, neural networks, artificial intelligence, machine learning, and the primary topic of the text, that is, fuzzy systems. This chapter explores learn two forms of logic and reasoning called crisp logic or reasoning and fuzzy logic or reasoning. Fuzzy logic has been found to be extremely beneficial and useful to people involved in research and development in numerous fields including engineers, computer software developers, mathematicians, medical researchers, and natural scientists. Fuzzy logic, with roots in early Greek philosophy, finds a wide variety of contemporary applications ranging from the manufacture of cement to the control of high-speed trains, auto focus cameras, and potentially self-driving automobiles. Expert systems are an outgrowth of postproduction systems augmented with various elements of probability theory and fuzzy logic to emulate human reasoning within constrained domains.