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Introduction to Artificial Intelligence

  • Textbook
  • © 2017


  • An ideal, quick resource on A.I., excellent for self-study
  • Presents an application-focused and hands-on approach to learning the subject
  • Provides study exercises at the end of each chapter, in addition to highlighted examples, definitions, theorems, and illustrative cartoons
  • Updated second edition featuring new material on deep learning

Part of the book series: Undergraduate Topics in Computer Science (UTICS)

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Table of contents (11 chapters)


About this book

This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning.

Topics and features: presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and solutions, 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; reports on developments in deep learning, including applications of neural networks to generate creative content such as text, music and art (NEW); examines performance evaluation of clustering algorithms, and presents two practical examples explaining Bayes’ theorem and its relevance in everyday life (NEW); discusses search algorithms, analyzing the cycle check, explaining route planning for car navigation systems, and introducing Monte Carlo Tree Search (NEW); includes a section in the introduction on AI and society, discussing the implications of AI on topics such as employment and transportation (NEW).

Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material.

Authors and Affiliations

  • Hochschule Ravensburg-Weingarten, Weingarten, Germany

    Wolfgang Ertel

About the author

Dr. Wolfgang Ertel is a professor at the Institute for Artificial Intelligence at the Ravensburg-Weingarten University of Applied Sciences, Germany.

Bibliographic Information

  • Book Title: Introduction to Artificial Intelligence

  • Authors: Wolfgang Ertel

  • Translated by: Nathanael T. Black

  • Series Title: Undergraduate Topics in Computer Science

  • DOI:

  • Publisher: Springer Cham

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

  • Copyright Information: Springer International Publishing AG 2017

  • Softcover ISBN: 978-3-319-58486-7Published: 29 January 2018

  • eBook ISBN: 978-3-319-58487-4Published: 18 January 2018

  • Series ISSN: 1863-7310

  • Series E-ISSN: 2197-1781

  • Edition Number: 2

  • Number of Pages: XIV, 356

  • Number of Illustrations: 84 b/w illustrations, 46 illustrations in colour

  • Topics: Artificial Intelligence

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