AI Game Engine Programming

  • 11h 58m
  • Brian Schwab
  • Cengage Course PTR
  • 2009

A fully revised update to the first edition, AI Game Engine Programming, Second Edition provides game developers with the tools and information they need to create modern game AI engines. Covering the four principle elements of game artificial intelligence, the book takes you from theory to actual game development, going beyond merely discussing how a technique might be used. Beginning with a clear definition of game AI, you'll learn common terminology, the underlying concepts of AI, and you'll explore the different parts of the game AI engine. You'll then take a look at AI design considerations, solutions, and even common pitfalls genre-by-genre, covering the majority of modern game genres and examining concrete examples of AI used in actual commercial games. Finally, you'll study actual code implementations for each AI technique presented, both in skeletal form and as part of a real-world example, to learn how it works in an actual game engine and how it can be optimized in the future. Written for experienced game developers with a working knowledge of C++, data structures, and object oriented programming, AI Game Engine Programming, Second Edition will expand your AI knowledge and skills from start to finish.

About the Author

Brian Schwab (San Diego, CA) has been a game programmer for over ten years, and has held key positions as Gameplay and AI Programmer for both Angel Studios and DreamWorks Interactive. He currently acts as Senior AI Programmer for Sony Computer Entertainment.

In this Book

  • Basic Definitions and Concepts
  • An AI Engine: The Basic Components and Design
  • AIsteroids: Our AI Test Bed
  • Role-Playing Games (RPGs)
  • Adventure Games
  • Real-Time Strategy (RTS) Games
  • First-Person Shooters/Third-Person Shooters (FTPS)
  • Platform Games
  • Shooter Games
  • Sports Games
  • Racing Games
  • Classic Strategy Games
  • Fighting Games
  • Miscellaneous Genres of Note
  • Finite-State Machines
  • Fuzzy-State Machines (FuSMs)
  • Message-Based Systems
  • Scripting Systems
  • Location-Based Information Systems
  • Steering Behaviors
  • Combination Systems
  • Genetic Algorithms
  • Neural Networks
  • Other Techniques of Note
  • Distributed AI Design
  • Common AI Development Concerns
  • Debugging
  • Conclusions, and the Future
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