Skip to main content

Introduction to Artificial Intelligence

  • Textbook
  • Jul 2024
  • Latest edition

Overview

  • A concise, quick resource on A.I., excellent for courses and professional self-study
  • Presents an application-focused and hands-on approach to learning the subject
  • Provides study exercises, highlighted examples, definitions, theorems, and illustrative cartoons

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

Buy print copy

Softcover Book USD 54.99
Price excludes VAT (USA)
This title has not yet been released. You may pre-order it now and we will ship your order when it is published on 25 Jul 2024.
  • Compact, lightweight edition
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

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 third 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 

·        Introduces convolutional neural networks as the currently most important type of deep learning networks with applications to image classification (NEW) 

·        Contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons 

·        Reports on developments in deep learning, including applications of neural networks to large language models as used in state-of-the-art chatbots as well as to the generation of music and art (NEW) 

·        Includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks, and reinforcement learning

 ·        Covers various classical machine learning algorithms and introduces important general concepts such as cross validation, data normalization, performance metrics and data augmentation (NEW)

·       Includes a section on AI and society, discussing the implications of AI on topics such as employment and transportation 

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.

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

 











Keywords

  • Artificial Intelligence
  • Agents
  • Logic
  • Search
  • Reasoning with Uncertainty
  • Machine Learning
  • Neural Networks

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, INVIDIA, tunguzreview.com)

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

  • Series Title: Undergraduate Topics in Computer Science

  • Publisher: Springer Wiesbaden

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

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2024

  • Softcover ISBN: 978-3-658-43101-3Due: 25 July 2024

  • eBook ISBN: 978-3-658-43102-0Due: 25 July 2024

  • Series ISSN: 1863-7310

  • Series E-ISSN: 2197-1781

  • Edition Number: 3

  • Number of Pages: XVIII, 384

  • Number of Illustrations: 188 b/w illustrations, 71 illustrations in colour

Publish with us