ARTIFICIAL INTELLIGENCE MICHAEL NEGNEVITSKY PDF

Negnevitsky shows students how to build intelligentsystems drawing on techniques from knowledge-based systems, neuralnetworks, fuzzy systems, evolutionary computation and now alsointelligent agents. The principles behind these techniques areexplained without resorting to complex mathematics, showing how thevarious techniques are implemented, when they are useful and whenthey are not. No particular programming language is assumed and thebook does not tie itself to any of the software tools available. However, available tools and their uses will be described andprogram examples will be given in Java.

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It favors natural language explanations over mathematical demonstrations, so it can be easily understood by everyone. 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 This is a highly readable book on its subject. 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.

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Artificial Intelligence

It favors natural language explanations over mathematical demonstrations, so it can be easily understood by everyone. 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 This is a highly readable book on its subject. 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.

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Artificial Intelligence: A Guide to Intelligent

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