The objective of the book you hold in your hands is to provide a solid and
practical foundation to game AI, giving you the confidence to approach
new challenges with excitement and optimism. AI is an enormous topic, so
don’t expect to come away from this book an expert, but you will have
learned the skills necessary to create entertaining and challenging AI for
the majority of action game genres. Furthermore, you will have a sound
understanding of the key areas of game AI, providing a solid base for any
further learning you undertake. And let me tell you, the learning process is
Being a good game AI programmer is not just about knowing how to
implement a handful of techniques. Of course, individual techniques are
important, but how they can be made to work together is more vital to the
AI development process. To this end, this book spends a lot of time walk-
ing you through the design of agents capable of playing a team sports game
(Simple Soccer) and a deathmatch type shoot-’em-up (Raven), demonstrat-
ing clearly how each technique is used and integrated with others.
Furthermore, Simple Soccer and Raven provide a convenient test bed for
further experimentation, and within the conclusions of many of the chap-
ters are suggestions for future exploration.
Academic AI vs. Game AI
There is an important distinction to be made between the AI studied by
academics and that used in computer games. Academic research is split
into two camps: strong AI and weak AI. The field of strong AI concerns
itself with trying to create systems that mimic human thought processes
and the field of weak AI (more popular nowadays) with applying AI tech
nologies to the solution of real-world problems. However, both of these
fields tend to focus on solving a problem optimally, with less emphasis on
hardware or time limitations. For example, some AI researchers are per
fectly happy to leave a simulation running for hours, days, or even weeks
on their 1000-processor Beowolf cluster so long as it has a happy ending
they can write a paper about. This of course is an extreme case, but you get
my point.
Game AI programmers, on the other hand, have to work with limited
resources. The amount of processor cycles and memory available varies

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