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. This book 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.
Review By: Dr. Tilmann Bruckhaus 03/16/2006M. Tim Jones’ book "AI Application Programming" is a practical and inspiring
introduction to a variety of artificial intelligence (AI) programming
techniques. This book is ideal for readers who want to become familiar with a
number of these techniques, without delving into too much detail on any one
Each chapter stands on its own, allowing the reader to focus on a small
number of techniques or skip over some entirely. The author reviews the code at
a fairly detailed level, and each programming technique’s source code of key
functions is reproduced. Every AI programming technique mentioned is also
illustrated with a variety of diagrams, tables, and session transcripts from
program runs. Another key feature of the book is the fairly broad selection of
techniques, which helps the reader appreciate the diversity of practical AI
programming. Jones reviews fifteen AI programming techniques, from Classifier
Systems to Simulated Annealing.
Jones begins the book by reviewing the history of AI from the 1940s to the
present and concludes with a review of the present state of AI. The majority of
the book is dedicated to the overview of programming techniques. His description
of each technique covers its purpose and motivation, who developed the
technique, and why. After this background, Jones gives a brief overview of how
the procedure operates, guided by diagrams and small example problems.
One of the most useful resources in the book is a simple implementation of
each technique in the C programming language. Jones walks the reader through
some functions of each implementation to illuminate how the idea turns into an
executable. The complete source code is provided on a CD that is included with
Jones first covers the A-Star pathfinding algorithm, followed by the newer
Simulated Annealing technique. He then covers the Particle Swarm Optimization
method that tracks moving targets, and the Adaptive Resonance Theory that finds
application in personalization solutions and helps recommend likely choices in
shopping application and other similar systems. The book also covers the equally
useful techniques of Neural Networks, Reinforcement Learning, Genetic
Algorithms, Artificial Life, Rule-Based Systems, Fuzzy Logic, Natural Language
Processing, Bigram Model, and finally Agent-Based Software.