Artificial Intelligence: A Guide to Intelligent Systems, 3RD EDITION Paperback – January 1, 2019

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.

Excellent scope of aspects of AI. Text book format with comprehensive summaries at the end of each chapter.

The author explains various AI concepts in very simple terms and has managed to present the math behind some of the ideas in an understandable manner.The treatment of various topics is intermediate though but it is a good place to start and does not leave the reader riddled with complex math equations.In-fact the author has done a great job at keeping the concepts separate from the mathematics, except for some places like neural networks where it is not possible to explain the concepts without talking about the math involved.Instead of focusing too much on a particular aspect of intelligent systems this book deals with a whole spectrum of technologies such as fuzzy systems, neural networks, hybrid systems etc.The writing style of the author is very simple and clear and it is possible to finish the entire book over a period of one semester or a little more.

I already had an e-book of this book, and got through the second chapter, so I wanted a physical copy. All of the other printed versions on Amazon were a bit pricy, but this was the cheapest option.Firstly, the contents of the book are fantastic, there's a reason I went out of my way to get a physical copy. It really does what it says on the tin, explain state-of-the-art AI concepts in simple, easy to understand ways without getting too much into math. Thanks to this book, I was able to write my own production rule system from scratch, only with the general knowledge this book gave me as well as some theory from implementations like ACT-R. And it covers production systems in the very second chapter (the first chapter is just a history lesson). I especially love how light it is on the math, because I really don't know much of it and I don't particularly care to learn. All I need is the theory, and I'm more than capable of writing the code to implement the architecture.However, it does say it's for people who know virtually nothing about programming, which I disagree with. I've been developing for over a decade and I don't think I could implement things like a production rule system without my years of experience. It was quite an engineering experiment for me and I had to invent a lot of things that a beginner would never think of. If you're a beginner, and you want to try writing a hybrid connectionist-symbolic cognitive architecture that uses production rule systems, I would put it on hold and instead start writing games from scratch. Writing a game engine will help you learn how to design a modular, fault-tolerant system that has some basic artificial intelligence in it already. Then you should try moving on to writing a cognitive architecture. There's way more published works and theory in writing game engines than AI, so there's a lot more for you to learn in that field, which will help you learn how to make any kind of software architecture, because you definitely need a lot of development theory to make a cognitive architecture. Games are a solved issue, AI is still highly experimental, so if you're still new at programming, I would go with games for now. I'm definitely not saying you shouldn't at least read this book because you will definitely learn interesting AI theory, but just know you'll have a very hard time actually trying to write any software that this book covers.Now, about this specific printed edition. The print isn't awful, but you do get what you pay for. The book is smaller than I expected, but perfectly readable. The pages are a little cheap but not too cheap. The printed text itself is often crooked and some words are faded. Some of the pages have bent corners and the cover had some scuffs. I assume I bought this brand new, but you could mistake it for being gently used. All in all, I'm happy with my purchase, it's more than good enough for me and I got to save a few dozen bucks. The only thing I don't understand is, on the upper left corner of the cover, it says "Circulation of this edition outside the Indian subcontinent is unauthorized." I live in the US, so I'm not sure how they got this over to me.

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.