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Algorithms and Architectures of Artificial Intelligence (Frontiers in Artificial Intelligence and Applications)

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This book gives an overview of methods developed in artificial intelligence for search, learning, problem solving and decision-making. It gives an overview of algorithms and architectures of artificial intelligence that have reached the degree of maturity when a method can be presented as an algorithm, or when a well-defined architecture is known, e.g. in neural nets and intelligent agents. It can be used as a handbook for a wide audience of application developers who are interested in using artificial intelligence methods in their software products. Parts of the text are rather independent, so that one can look into index and go directly to a description of a method presented in the form of an abstract algorithm or an architectural solution. The book can be used also as a textbook for a course in applied artificial intelligence. It has been used as a course material for this kind of courses on undergraduate and graduate levels at Tallinn University of Technology and Royal Institute of Technology in Stockholm. Exercises on the subject are added at the end of each chapter. Neither programming skills nor specific knowledge in computer science are expected from the reader. However, some parts of the text will be fully understood by those who know the terminology of computing well.

The algorithms developed in the field of artificial intelligence are often directly applicable in solving various difficult problems and, therefore, they constitute a valuable part of the artificial intelligence that can be used independently of the philosophical and deep theoretical considerations related to the research in this area. Most of the algorithms are presented in this book in a simple algorithmic language. Sometimes, e.g. when describing neurons in artificial neural nets, it has been more expressive to use common mathematical notations for presenting the functionality of entities. Taxonomy of algorithms and methods concerned is discussed at the end of each chapter, summarizing the material presented in it. This taxonomy can be a valuable aid in developing new algorithms by elaborating the presented ones.
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Decomposition Methodology For Knowledge Discovery And Data Mining: Theory And Applications
Decomposition Methodology For Knowledge Discovery And Data Mining: Theory And Applications
The book presents an interesting and pleasant introduction to the topic, which can guide the reader to the knowledge of the existing decomposition methods, and to the choice of those most promising for the problems he has to face. -- Zentralblatt MATH

Data Mining is the science and technology of exploring data in
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JavaScript Testing Beginner's Guide
JavaScript Testing Beginner's Guide

JavaScript is an important part of web development in today's Web 2.0 world. While there are many JavaScript frameworks in the market, learning to write, test, and debug JavaScript without the help of any framework will make you a better JavaScript developer. However, testing and debugging can be time consuming, tedious, and painful. This...

Strategic Supply Chain Management
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"We have to get a handle on our supply chain."

These words have become a standard corner-office lament in today's no-room-for-error business arena. But even when companies address their most glaring supply chain challenges, they can still find that cost-effective and strategic supply chain management is hard to...


Windows Runtime via C# (Developer Reference)
Windows Runtime via C# (Developer Reference)

Delve inside the Windows Runtime - and learn best ways to design and build Windows Store apps. Guided by Jeffrey Richter, a recognized expert in Windows and .NET programming, along with principal Windows consultant Maarten van de Bospoort, you'll master essential concepts. And you'll gain practical insights and tips for how to...

Practical Biomedical Signal Analysis Using MATLAB® (Series in Medical Physics and Biomedical Engineering)
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Practical Biomedical Signal Analysis Using MATLAB® presents a coherent treatment of various signal processing methods and applications. The book not only covers the current techniques of biomedical signal processing, but it also offers guidance on which methods are appropriate for a given task and...

Group Theoretical Methods in Image Processing (Lecture Notes in Computer Science)
Group Theoretical Methods in Image Processing (Lecture Notes in Computer Science)

These Lecture Notes are based on a series of lectures I gave at the Linkoping University Department of Electrical Engineering in 1988. In these lectures 1 tried to give an overview of the theory of representation of compact groups and some applications in the fields of image science and pattern recognition.

The participants...

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