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Fundamentals of the New Artificial Intelligence

Neural, Evolutionary, Fuzzy and More

  • Textbook
  • © 2008

Overview

Editors:
  1. Toshinori Munakata

    1. Computer and Information Science Department, Cleveland State University, Cleveland, USA

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  • No other books emphasize technical fundamentals of newer AI areas
  • New sections, such as that on Boltzmann Machines, contain easy-to-understand descriptions and algorithms, following the features on the original edition

Part of the book series: Texts in Computer Science (TCS)

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Table of contents (7 chapters)

  1. Front Matter

    Pages I-XI
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  2. Introduction

    • Toshinori Munakata
    Pages 1-6

  3. Neural Networks: Fundamentals and the Backpropagation Model

    • Toshinori Munakata
    Pages 7-36

  4. Neural Networks: Other Models

    • Toshinori Munakata
    Pages 37-84

  5. Genetic Algorithms and Evolutionary Computing

    • Toshinori Munakata
    Pages 85-120

  6. Fuzzy Systems

    • Toshinori Munakata
    Pages 121-161

  7. Rough Sets

    • Toshinori Munakata
    Pages 162-205

  8. Chaos

    • Toshinori Munakata
    Pages 206-245

  9. Back Matter

    Pages 247-255
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Keywords

About this book

The book covers the most essential and widely employed material in each area, particularly the material important for real-world applications. Our goal is not to cover every latest progress in the fields, nor to discuss every detail of various techniques that have been developed. 

New sections/subsections added in this edition are: Simulated Annealing (Section 3.7), Boltzmann Machines (Section 3.8) and Extended Fuzzy if-then Rules Tables (Sub-section 5.5.3). Also, numerous changes and typographical corrections have been made throughout the manuscript. The Preface to the first edition follows. General scope of the book Artificial intelligence (AI) as a field has undergone rapid growth in diversification and practicality. For the past few decades, the repertoire of AI techniques has evolved and expanded. Scores of newer fields have been added to the traditional symbolic AI. Symbolic AI covers areas such as knowledge-based systems, logical reasoning, symbolic machine learning, search techniques, and natural language processing. The newer fields include neural networks, genetic algorithms or evolutionary computing, fuzzy systems, rough set theory, and chaotic systems.

Reviews

From the reviews of the second edition:

"The book focuses on five important areas in computer science: neural networks, genetic algorithms, fuzzy systems, rough sets, and chaos. … This is an excellent textbook for undergraduate and graduate students in computer science, coming to this subject for the first time and desiring to acquire a comprehensive view of the whole area of soft computing. The mathematical background required is minimal … . Critical comparisons among the models illustrated are suggested, and essential literature references are given for further reading." (G. Guida, ACM Computing Reviews, October, 2008)

Editors and Affiliations

  • Computer and Information Science Department, Cleveland State University, Cleveland, USA

    Toshinori Munakata

Bibliographic Information

  • Book Title: Fundamentals of the New Artificial Intelligence

  • Book Subtitle: Neural, Evolutionary, Fuzzy and More

  • Editors: Toshinori Munakata

  • Series Title: Texts in Computer Science

  • DOI: https://doi.org/10.1007/978-1-84628-839-5

  • Publisher: Springer London

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer-Verlag London Ltd., part of Springer Nature 2008

  • Hardcover ISBN: 978-1-84628-838-8Published: 21 February 2008

  • Softcover ISBN: 978-1-4471-6803-4Published: 21 February 2008

  • eBook ISBN: 978-1-84628-839-5Published: 01 January 2008

  • Series ISSN: 1868-0941

  • Series E-ISSN: 1868-095X

  • Edition Number: 2

  • Number of Pages: XI, 256

  • Topics: Artificial Intelligence, Data Mining and Knowledge Discovery, Pattern Recognition

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