AI Application Programming

by M. Tim Jones

In the second edition of this bestseller, the author continues to demystify the techniques associated with the field of artificial intelligence. It covers a wide variety of techniques currently defined as "AI" and shows how they can be useful in practical, everyday applications. AI Application Programming covers both the theory and the practical applications to teach developers how to apply AI techniques in their own designs. Each chapter covers both the theory of the algorithm or the technique under discussion followed by a practical application of the technique with a detailed discussion of the source code.

Genres: Programming, Artificial Intelligence, Nonfiction, Technology, Science, Technical

496 pages, Paperback

First published March 27, 2003

About the author

M. Tim Jones is a product architect and engineering author specializing in virtualization, Linux, Linux internals, programming, network protocols, embedded development, and artificial intelligence. Over the past decade, he has written five books, two of which have been released in second editions. His publications focus on networking protocols, Sockets programming, artificial intelligence, and Linux user-space programming. His work includes book descriptions, errata, and various online publications that explore these technical domains.

Reviews

[Bill's Chaos · Rating 3 out of 5]

This book came out a while before the recent Deep Learning revolution. There is a chapter on neural networks and another on Reinforcement Learning, which are important components of Deep Learning.

The code is written in C which should make it more portable, but I found most of the example programs will not compile in Visual Studio 2019. The problems look like they should be easy enough to fix. Many macros contain type casting problems, and functions used for file I/O are marked as obsolete because of security issues. All except the last example are console based which eliminates much of the incompatibility issues found with the code in most older books, when using it with modern systems.

I had problems with the code in the first edition of this book. I can't remember exactly what the problem was, but it was probably the casting problem in the macros. I sent him an email about this and he put my name in the acknowledgments for this book.

I purchased the book when it came out, about 14 years ago, but didn't get around to reading it until now.

[Nick Gotch · Rating 4 out of 5]

Anyone looking to learn AI programming should read this book. It's somewhat beginner but covers basic concepts every AI developer should know and also gets into some more advanced topics. The only down-side to it is that the code samples are in plain C (mostly) so no fancy high-level code to make things easier.

[Jac · Rating 4 out of 5]

Very quick introduction to a few algorithms, most of the book is showing and explaining the source code needed to implement them. Good for someone without much AI familiarity who wants to build something. Would have been a useful companion textbook for my AI class, but doesn't have much theory in it.