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Rating: 
Summary: Great Introductory Book on Soft Computing
Review: For a beginner that wants to know where the stories about Soft Computing really converge, this book is a starting point. The style of the author is simple and great. My interest was to get a book that keeps the daunting mathematical jargons in Fuzzy Logic (contained in several other books) minimal, while presenting the concepts. I fell in love with this book, that I had to run through all the pages as if it's a novel. This book really demonstrates that the whole idea behind intelligent systems are simple and straightforward. You do not need another teacher. He presented algorithms (e.g. back-propagation)in a very simple to understand manner. Dr. Michael Negnevitsky, the author, must be a great teacher. It's a handy and nice book. I strongly recommend it.
Rating:
Summary: Excellent Treatment of Complex Topics
Review: What Dr. Negnevitsky states in the preface of this book, "Most of the literature on AI is expressed in the jargon of computer science, and crowded with complex matrix algebra and differential equations" is an accurate assessment of current textbooks that try to go beyond just the basics of AI. Actually, this book does contain some of the same complex material that Dr. Negnevitsky accuses others for having with one exception: He does a terrific job in simplifying the complex theories behind them. At first, when I flipped through the pages, huge equations and matrices jumped at me. My first impression was that this book was for serious computer scientists or mathematicians. I was looking for simpler material for my beginning AI students. I started reading the preface and found the argument interesting. I speed-read through the first chapter and found the history of the field presented in a concise and a very well laid out fashion. I jumped into reading the beginning of chapter 2 and I was amazed at how well Dr. Negnevitsky progressed from basic ideas to more and more complex layers. With other similar books, the reader will need many basic theory books (mathematics, basic AI...) in order to understand the topics. Dr. Negnevitsky provides all the basics necessary. This same strategy is repeated for the remaining chapters. I acquired the book and read it from beginning to end. I found the material consistently well presented. One warning: this book does get very technical and complex in many chapters. However, the material in each of those chapters is progressively laid out. Even if a reader stops in the middle of some chapters, there is still a lot to gain from the experience of reading the entire book. I highly recommend it to anyone interested in really understanding beyond just keywords and delve into the internals of AI topics. Thanks to Dr. Negnevitsky for a great book.
Rating:
Summary: Excellent Treatment of Complex Topics
Review: What Dr. Negnevitsky states in the preface of this book, "Most of the literature on AI is expressed in the jargon of computer science, and crowded with complex matrix algebra and differential equations" is an accurate assessment of current textbooks that try to go beyond just the basics of AI. Actually, this book does contain some of the same complex material that Dr. Negnevitsky accuses others for having with one exception: He does a terrific job in simplifying the complex theories behind them. At first, when I flipped through the pages, huge equations and matrices jumped at me. My first impression was that this book was for serious computer scientists or mathematicians. I was looking for simpler material for my beginning AI students. I started reading the preface and found the argument interesting. I speed-read through the first chapter and found the history of the field presented in a concise and a very well laid out fashion. I jumped into reading the beginning of chapter 2 and I was amazed at how well Dr. Negnevitsky progressed from basic ideas to more and more complex layers. With other similar books, the reader will need many basic theory books (mathematics, basic AI...) in order to understand the topics. Dr. Negnevitsky provides all the basics necessary. This same strategy is repeated for the remaining chapters. I acquired the book and read it from beginning to end. I found the material consistently well presented. One warning: this book does get very technical and complex in many chapters. However, the material in each of those chapters is progressively laid out. Even if a reader stops in the middle of some chapters, there is still a lot to gain from the experience of reading the entire book. I highly recommend it to anyone interested in really understanding beyond just keywords and delve into the internals of AI topics. Thanks to Dr. Negnevitsky for a great book.
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