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Table of contents

  1. Front Matter
    Pages I-XI
  2. Wolfgang Ertel
    Pages 1-14
  3. Wolfgang Ertel
    Pages 15-30
  4. Wolfgang Ertel
    Pages 31-55
  5. Wolfgang Ertel
    Pages 57-65
  6. Wolfgang Ertel
    Pages 67-82
  7. Wolfgang Ertel
    Pages 83-111
  8. Wolfgang Ertel
    Pages 113-160
  9. Wolfgang Ertel
    Pages 161-220
  10. Wolfgang Ertel
    Pages 221-256
  11. Wolfgang Ertel
    Pages 257-277
  12. Wolfgang Ertel
    Pages 279-303
  13. Back Matter
    Pages 305-316

About this book

Introduction

The ultimate aim of artificial intelligence (A.I.) is to understand intelligence and to build intelligent software and robots that come close to the performance of humans. On their way towards this goal, A.I. researchers have developed a number of quite different subdisciplines.

This concise and accessible Introduction to Artificial Intelligence supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The textbook presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning.

Topics and features:

  • Presents an application-focused and hands-on approach to learning the subject
  • Provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book
  • Supports the text with highlighted examples, definitions, theorems, and illustrative cartoons
  • Includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning
  • Contains an extensive bibliography for deeper reading on further topics
  • Supplies additional teaching resources, including lecture slides and training data for learning algorithms, at the website http://www.hs-weingarten.de/~ertel/aibook

Students of computer science and other technical natural sciences will find this easy-to-read textbook excellent for self-study, a high-school level of knowledge of mathematics being the only prerequisite to understanding the material. With its extensive tools and bibliography, it is an ideal, quick resource on A.I.

Dr. Wolfgang Ertel is a professor at the Collaborative Center for Applied Research on Service Robotics at the Ravensburg-Weingarten University of Applied Sciences, Germany.

Keywords

Artificial Intelligence

Authors and affiliations

  1. 1.FB Elektrotechnik und InformatikFH Ravensburg-WeingartenWeingartenGermany

About the authors

Dr. Wolfgang Ertel is a professor at the Collaborative Center for Applied Research on Service Robotics at the Ravensburg-Weingarten University of Applied Sciences, Germany.

Bibliographic information

  • Book Title Introduction to Artificial Intelligence
  • Authors Wolfgang Ertel
  • Series Title Undergraduate Topics in Computer Science
  • DOI https://doi.org/10.1007/978-0-85729-299-5
  • Copyright Information Springer-Verlag London Limited 2011
  • Publisher Name Springer, London
  • eBook Packages Computer Science Computer Science (R0)
  • Softcover ISBN 978-0-85729-298-8
  • eBook ISBN 978-0-85729-299-5
  • Series ISSN 1863-7310
  • Edition Number 1
  • Number of Pages XII, 316
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Artificial Intelligence
  • Buy this book on publisher's site
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Reviews

“The book overall is very readable and relevant. One of the most valuable aspects of this book are the worked out examples and numerous (solved) exercises. … Overall, this is a very well written and pedagogical book that fills an important niche in the Artificial Intelligence educational literature. Highly recommended.” (Bojan Tunguz, tunguzreview.com, July, 2015)

“This accessible and concise introduction to the field of artificial intelligence (AI) is intended primarily for self-study or as a foundation of a short course on the subject. The book consists of ten topic chapters, each one of which offers an extended list of exercises. Chapter 11 contains solutions to all exercises. Additional teaching resources, including lecture slides, are available on the book website.” (Neli Zlatareva, Zentralblatt MATH, Vol. 1238, 2012)

“The book is aimed primarily at undergraduates who have not yet taken linear algebra or multidimensional calculus. … it contains many exercises with solutions at the back; thus, it supports self-learning. … The many excellent figures, some in color, help make the material easily understandable. A companion Web site contains supplementary materials, such as program code for the book, most of which is in or commented on in German. Summing Up: Recommended. Upper-division undergraduates and above.” (S. L. Tanimoto, Choice, Vol. 49 (2), October, 2011)