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Artificial Intelligence: A Guide to Intelligent Systems
Provides a practical introduction to artificial intelligence that is less mathematically rigorous than other books on the market. Appropriate for programmers looking for an overview of all facets of artificial intelligence.
394 pages, Hardcover
First published August 30, 2001
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Displaying 1 - 8 of 8 reviews
August 9, 2020
I am looking for the best textbook for AI, and I choose this book, simply because its written in 2001, about 20 years ago, around the same time when I start my computer science degree. AI back then is very different than now, so this is very good book for old person like me to understand what is going on in the AI world. This book is the best book so far because its start with Expert System, things that very happening in 1990s period, where almost no one talk about Machine Learning -what so called more populer in AI nowadays.
The third chapter after introduction and expert system, is uncertainty. "One of the common characteristics of the information available to human experts is its imperfection. Information can be incomplete, inconsistent, uncertain, or all three. In other words, information is often unsuitable for solving a problem"
The fourth is fuzzy. "Fuzzy logic is based on the idea that all things admit of degrees"
The fifth is frame, I am familiar with this.
The sixth is machine learning, but at that time, no one talk about machine learning, everybody talk either as neural network or as genetic algorithm. Basically is "adaptive mechanisms that enable computers to learn from experience, learn by example and learn by analogy."
Expert system: anything can be solved in 10-30 minutes of inhouse expert system
Fuzzy: Classification e.g mortgage
Neural Network: Recognition e.g character recognition
The third chapter after introduction and expert system, is uncertainty. "One of the common characteristics of the information available to human experts is its imperfection. Information can be incomplete, inconsistent, uncertain, or all three. In other words, information is often unsuitable for solving a problem"
The fourth is fuzzy. "Fuzzy logic is based on the idea that all things admit of degrees"
The fifth is frame, I am familiar with this.
The sixth is machine learning, but at that time, no one talk about machine learning, everybody talk either as neural network or as genetic algorithm. Basically is "adaptive mechanisms that enable computers to learn from experience, learn by example and learn by analogy."
Expert system: anything can be solved in 10-30 minutes of inhouse expert system
Fuzzy: Classification e.g mortgage
Neural Network: Recognition e.g character recognition
March 8, 2018
A simpler book than most of the other ones that are usually suggested to people interested in artificial intelligence, but that doesn't mean it's any less valid. It favors natural language explanations over mathematical demonstrations, so it can be easily understood by everyone. Overall the lack of proper maths implies that anyone willing to extend upon the knowledge the book offers will have to use other sources alongside it, but personally it's how I think this book shines.
A big advantage over many other AI textbooks is that it's actually up to date with the current tech (as of the writing of this review), so it gives good explanations on systems, like fuzzy logic-based ones, that others ignore or just quote in a small paragraph, indicating how they still need to mature.
A big advantage over many other AI textbooks is that it's actually up to date with the current tech (as of the writing of this review), so it gives good explanations on systems, like fuzzy logic-based ones, that others ignore or just quote in a small paragraph, indicating how they still need to mature.
December 18, 2016
This is a highly readable book on its subject. It is by no means a book on "coding" AI systems. Nor is it a math tomb, though there is more math than code. It is first and foremost an overview of the different technologies that sit inside the AI toolkit, including expert systems, fuzzy stems and neural networks - and how they can likely be combined to address shortcomings and potential rewards.
The amount of math is not daunting, and is helpful for understanding the foundations of the different systems. Since the aim of the book is not coding up specific examples, but closer to presenting cases as well as a process cookbook, this mathematical foundational is helpful.
I have enjoyed this book immensely, likely my favorite book on AI technology so far. While other books may try to provide working examples for the student, this book is more like an aged tutor explaining the core of the subject, with all the wisdom of repeated failure and startling success time brings. It certainly is not exhaustive in detail, but this book will be one to go back to when you are lost in the weeds.
The amount of math is not daunting, and is helpful for understanding the foundations of the different systems. Since the aim of the book is not coding up specific examples, but closer to presenting cases as well as a process cookbook, this mathematical foundational is helpful.
I have enjoyed this book immensely, likely my favorite book on AI technology so far. While other books may try to provide working examples for the student, this book is more like an aged tutor explaining the core of the subject, with all the wisdom of repeated failure and startling success time brings. It certainly is not exhaustive in detail, but this book will be one to go back to when you are lost in the weeds.
February 15, 2013
it is a wonderful book .. it has all the basic concept of the expert systems in a simple way.. very interesting i used it as my background in the expert system course during my MSc study
i recommended it for any student that want to learn every thing in expert system in an easy interesting frame
i recommended it for any student that want to learn every thing in expert system in an easy interesting frame
October 9, 2013
very simple , clear , good examples
November 14, 2013
A touch of Max Headroom and the lawnmower man.
January 27, 2020
Negnevitsky made artificial intelligence (AI) easy to understand. This is a great book for beginning AI scientists.
Displaying 1 - 8 of 8 reviews