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Introduction to Artificial Intelligence (Undergraduate Topics in Computer Science), by Wolfgang Ertel
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This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book 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, and theorems; 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 an associated website.
- Sales Rank: #840059 in eBooks
- Published on: 2011-03-18
- Released on: 2011-03-18
- Format: Kindle eBook
Review
“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)
From the Back Cover
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.
About the Author
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.
Most helpful customer reviews
3 of 3 people found the following review helpful.
Great Introduction
By Blue Chip
In a very short, clear and concise method, this book covers all of the foundational topics for artificial intelligence. As a graduate student I used the book "Artificial Intelligence a Modern Approach". That textbook is a thorough introduction that thoroughly explains the theory and the implementation of artificial intelligence topics.
This book is, as it says, an introduction. For those who are completely unfamiliar with computer science topics, such as search algorithms like Dijkstra's Algorithm, Euler paths, depth first search, breadth first search, etc., this book might be too advanced. In other words, I feel the book assumes the reader is versed in computer science topics. Even without in depth computer science knowledge this book is an interesting read.
This book, as one can see from the table of contents, does a good job of introducing the reader to the foundational topics in artificial intelligence. I especially liked the fact that the book included a concise comparison of the previously mentioned search algorithms to iterative deepening, A* and heuristic search (informed vs. uninformed).
After reading "Artificial Intelligence a Modern Approach" I have found that this book, when considering the size and short concise writing style, is a handy reference to have around.
Well done Mr. Ertel.
5 of 7 people found the following review helpful.
Generally Unclear
By EST
Everything seemed somewhat unclear, so I felt that I never knew precisely what the author was saying. The first chapter was the worst. He was trying to show the equivalence of two types of logic, but I couldn't tell the difference. I quickly decided to skip the rest of the chapter.
At least some of the book's flaws were due to missing translation. For example, a section on logic started with values t and f (presumably for "true" and "false") but on the next page switched to using w and f (probably for "wahr" and "falsch"). If I didn't know these German words, this switch would really have thrown me. Another section talked about getting the consecutive pairs of letters from a name. For Henry, the pairs were "ha", "an" and "ns". Obviously, the name originally was "Hans".
I've dealt with some books that were a struggle to read and I still got nothing out of them. This book is not like that. It was easy to read and I got something from it, just not as much as I'd hoped.
1 of 1 people found the following review helpful.
Interesting survey of the current state of Artificial Intelligence. ...
By bradxt
Interesting survey of the current state of Artificial Intelligence. Be aware that the author presumes a solid background in symbolic logic and set notation. If the reader does not have this background, the symbolic logic equations that make up much of the meat of the content will be unintelligible. It may not be accurate to title this book as an Introduction as it may cause readers to assume it is an introductory level read. It is not.
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