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. The lack of assumed priorknowledge makes this book ideal for any introductory courses inartificial intelligence or intelligent systems design, while thecontemporary coverage means more advanced students will benefit bydiscovering the latest state-of-the-art techniques. For Sale in Indiansubcontinent only No mathematical or programming prerequisites.

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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. The lack of assumed priorknowledge makes this book ideal for any introductory courses inartificial intelligence or intelligent systems design, while thecontemporary coverage means more advanced students will benefit bydiscovering the latest state-of-the-art techniques.

For Sale in Indiansubcontinent only No mathematical or programming prerequisites. Linked coverage of all the latest artificial intelligence topics. Question and answer format. An emphasis on creating practical applications from hybrid techniques. Negnevitsky shows students how to build intelligent systems drawing on techniques from knowledge-based systems, neural networks, fuzzy systems and evolutionary computation and now also intelligent agents.

No mathematical or programming prerequisites. Rule-Based Expert Systems 3.

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Artificial Intelligence: A Guide to Intelligent Systems

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.

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