Another book on artificial intelligence . . . I’ve already seen so many of them. Why should I bother with this one? What makes this book different from the others? Each year hundreds of books and doctoral theses extend our knowledge of computer, or artificial, intelligence. Expert systems, artificial neural networks, fuzzy systems and evolutionary computation are major technologies used in intelligent systems. Hundreds of tools support these technologies, and thousands of scientific papers continue to push their boundaries. The contents of any chapter in this book can be, and in fact is, the subject of dozens of monographs. However, I wanted to write a book that would explain the basics of intelligent systems, and perhaps even more importantly, eliminate the fear of artificial intelligence. Most of the literature on artificial intelligence is expressed in the jargon of computer science, and crowded with complex matrix algebra and differential equations. This, of course, gives artificial intelligence an aura of respectability, and until recently kept non-computer scientists at bay. But the situation has changed! The personal computer has become indispensable in our everyday life. We use it as a typewriter and a calculator, a calendar and a communication system, an interactive database and a decision-support system. And we want more. We want our computers to act intelligently! We see that intelligent systems are rapidly coming out of research laboratories, and we want to use them to our advantage. What are the principles behind intelligent systems? How are they built? What are intelligent systems useful for? How do we choose the right tool for the job? These questions are answered in this book. Unlike many books on computer intelligence, this one shows that most ideas behind intelligent systems are wonderfully simple and straightforward. The book is based on lectures given to students who have little knowledge of calculus. And readers do not need to learn a programming language! The material in this book has been extensively tested through several courses taught by the author for the past decade. Typical questions and suggestions from my students influenced the way this book was written. The book is an introduction to the field of computer intelligence. It covers rule-based expert systems, fuzzy expert systems, frame-based expert systems, artificial neural networks, evolutionary computation, hybrid intelligent systems and knowledge engineering. The book also has an appendix and a glossary. The appendix provides a list of commercially available AI tools. The glossary contains definitions of over 250 terms used in expert systems, fuzzy logic, neural networks, evolutionary computation, knowledge engineering and data mining. I hope that the reader will share my excitement on the subject of artificial intelligence and soft computing and will find this book useful.
This book is great for beginners who want to understand the very fundamentals of AI and closely related topics such as expert systems or evolutionary algorithms, without going into too much details of the maths. Still, the book includes many mathematical examples and pseudocodes, which makes it even richer. My only problem with this book was the formatting. It did not work properly on Kindle unfortunately. I had to find the PDF of it to read the equations and to see the figures. It should be fixed.