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"AI for Game Developers": Chasing, Evading, Swarming, and More

August 26, 2004

Sebastopol, CA--From the ghosts in the classic arcade game Pac Man to the bots in the first-person shooter Unreal and many others in between, most games incorporate some form of artificial intelligence (AI). The definition of AI can vary broadly depending on whom you ask, but is often considered the ability of a computer or machine to exhibit behavior that is typically thought to require intelligence. Some definitions go even further, arguing that it's not enough to be able to reason and solve problems intelligently, but AI must also learn and adapt to be considered intelligence. AI that meets these requirements is termed "strong AI," contrasted with game AI, which is considered "weak AI."

As David M. Bourg and Glenn Seemann, authors of AI for Game Developers (O'Reilly, US $39.95) note, "The bottom line is that the definition of game AI is rather broad and flexible. Anything that gives the illusion of intelligence to an appropriate level, thus making the game more immersive, challenging, and most importantly, fun, can be considered game AI." Like the use of real physics in games, the authors maintain, good AI adds to the overall experience of the game, drawing players in and suspending their reality for a time.

Indeed, today's game players have grown in sophistication, no longer wowed by dazzling and compelling 3D graphics that were only dreamed of years ago. Fortunately, advanced AI game techniques are within the grasp of every game developer--not just those who dedicate their careers to AI. "AI for Game Developers" introduces novice game programmers and experienced programmers who are new to AI to a wide range of impressive game AI techniques such as finite state machines, fuzzy logic, and neural networks.

Written in straightforward, easy-to-understand language, and supported with code samples (written in C/C++) throughout, the book instructs readers in basic game behaviors, from chasing and evading, to pattern movement and flocking, to anticipating player moves. Readers are shown how to apply AI techniques to give their game characters believable intelligence by employing a mix of deterministic (traditional) and non-deterministic (newer) AI techniques aimed squarely at beginning AI developers.

Other topics covered in the book include:

  • Handling chasing, evading, swarming, and obstacle avoidance using a single technique based on potential functions
  • Solving pathfinding problems using several techniques, including waypoints and the venerable A* algorithm
  • Extending a game's underlying AI and exposing the AI engine to designers and players using AI scripting
  • Giving your game characters reasoning capabilities with rule-based AI, including fuzzy logic and finite state machines
  • Dealing with uncertainty by applying basic probability and advanced techniques such as Bayesian inference
  • Most books about game AI are geared toward experienced AI programmers and focus on relatively specific and advanced topics, effectively placing sophisticated AI techniques out of the reach of programmers who may not have the time or resources to dedicate themselves to tackling this vast field of study. But those who are new to game programming or experienced game programmers who need to get up to speed quickly on AI techniques will find "AI for Game Developers" to be the perfect starting point for understanding and applying AI techniques to their games.

    Additional Resources:

    AI for Game Developers
    David M. Bourg, Glenn Seemann
    ISBN 0-596-00555-5, 371 pages, $39.95 US, $57.95 CA
    1-800-998-9938; 1-707-827-7000

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