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Game AI Pro
Collected Wisdom of Game AI Professionals




ISBN 9781466565968
Published September 11, 2013 by A K Peters/CRC Press
598 Pages 139 B/W Illustrations

 
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Book Description

Successful games merge art and technology in truly unique ways. Fused under tight production deadlines and strict performance requirements, shaped by demanding player expectations, games are among the most complex software projects created today. Game AI Pro: Collected Wisdom of Game AI Professionals covers both the art and the technology of game AI. Nothing covered is theory or guesswork. The book brings together the accumulated wisdom, cutting-edge ideas, and clever tricks and techniques of 54 of today’s top game AI professionals. Some chapters present techniques that have been developed and passed down within the community for years while others discuss the most exciting new research and ideas from today’s most innovative games.

The book includes core algorithms that you’ll need to succeed, such as behavior trees, utility theory, spatial representation, path planning, motion control, and tactical reasoning. It also describes tricks and techniques that will truly bring your game to life, including perception systems, social modeling, smart camera systems, player prediction, and even an AI sound designer. Throughout, the book discusses the optimizations and performance enhancements that enable your game to run while maintaining 60 frames per second.

Table of Contents

General Wisdom
What Is Game AI?
Kevin Dill

Informing Game AI through the Study of Neurology
Brett Laming

Advanced Randomness Techniques for Game AI: Gaussian Randomness, Filtered Randomness, and Perlin Noise
Steve Rabin, Jay Goldblatt, and Fernando Silva

Architecture
Behavior Selection Algorithms: An Overview
Michael Dawe, Steve Gargolinski, Luke Dicken, Troy Humphreys, and Dave Mark

Structural Architecture—Common Tricks of the Trade
Kevin Dill

The Behavior Tree Starter Kit
Alex J. Champandard and Philip Dunstan

Real-World Behavior Trees in Script
Michael Dawe

Simulating Behavior Trees: A Behavior Tree/Planner Hybrid Approach
Daniel Hilburn

An Introduction to Utility Theory
David “Rez” Graham

Building Utility Decisions into Your Existing Behavior Tree
Bill Merrill

Reactivity and Deliberation in Decision-Making Systems
Carle Côté

Exploring HTN Planners through Example
Troy Humphreys

Hierarchical Plan-Space Planning for Multiunit Combat Maneuvers
William van der Sterren

Phenomenal AI Level-of-Detail Control with the LOD Trader
Ben Sunshine-Hill

Runtime Compiled C++ for Rapid AI Development
Doug Binks, Matthew Jack, and Will Wilson

Plumbing the Forbidden Depths: Scripting and AI
Mike Lewis

Movement and Pathfinding
Pathfinding Architecture Optimizations
Steve Rabin and Nathan Sturtevant

Choosing a Search Space Representation
Nathan R. Sturtevant

Creating High-Order Navigation Meshes through Iterative Wavefront Edge Expansions
D. Hunter Hale and G. Michael Youngblood

Precomputed Pathfinding for Large and Detailed Worlds on MMO Servers
Fabien Gravot, Takanori Yokoyama, and Youichiro Miyake

Techniques for Formation Movement using Steering Circles
Stephen Bjore

Collision Avoidance for Preplanned Locomotion
Bobby Anguelov

Crowd Pathfinding and Steering Using Flow Field Tiles
Elijah Emerson

Efficient Crowd Simulation for Mobile Games
Graham Pentheny

Animation-Driven Locomotion with Locomotion Planning
Jarosław Ciupiński

Strategy and Tactics
Tactical Position Selection: An Architecture and Query Language
Matthew Jack

Tactical Pathfinding on a NavMesh
Daniel Brewer

Beyond the Kung-Fu Circle: A Flexible System for Managing NPC Attacks
Michael Dawe

Hierarchical AI for Multiplayer Bots in Killzone 3
Remco Straatman, Tim Verweij, Alex Champandard, Robert Morcus, and Hylke Kleve

Using Neural Networks to Control Agent Threat Response
Michael Robbins

Agent Awareness and Knowledge Representation
Crytek’s Target Tracks Perception System
Rich Welsh

How to Catch a Ninja: NPC Awareness in a 2D Stealth Platformer
Brook Miles

Asking the Environment Smart Questions
Mieszko Zielinski

A Simple and Robust Knowledge Representation System
Phil Carlisle

A Simple and Practical Social Dynamics System
Phil Carlisle

Breathing Life into Your Background Characters
David “Rez” Graham

Alibi Generation: Fooling All the Players All the Time
Ben Sunshine-Hill

Racing
An Architecture Overview for AI in Racing Games
Simon Tomlinson and Nic Melder

Representing and Driving a Race Track for AI Controlled Vehicles
Simon Tomlinson and Nic Melder

Racing Vehicle Control Systems using PID Controllers
Nic Melder and Simon Tomlinson

The Heat Vision System for Racing AI: A Novel Way to Determine Optimal Track Positioning
Nic Melder

A Rubber-Banding System for Gameplay and Race Management
Nic Melder

Odds and Ends
An Architecture for Character-Rich Social Simulation
Michael Mateas and Josh McCoy

A Control-Based Architecture for Animal Behavior
Michael Ramsey

Introduction to GPGPU for AI
Conan Bourke and Tomasz Bednarz

Creating Dynamic Soundscapes Using an Artificial Sound Designer
Simon Franco

Tips and Tricks for a Robust Third-Person Camera System
Eric Martel

Implementing N-Grams for Player Prediction, Procedural Generation, and Stylized AI
Joseph Vasquez II

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Editor(s)

Biography

Steve Rabin is a principal software engineer at Nintendo of America, where he researches new techniques for Nintendo’s current and future platforms, architects development tools, and supports Nintendo developers. He also teaches game AI at the DigiPen Institute of Technology. He was previously an AI engineer at several start-up companies, including Gas Powered Games, WizBang Software Productions, and Surreal Software. He is the founder of the professional group AI Game Programmers Guild, with over 350 members worldwide. He earned a BS in computer engineering and an MS in computer science, both from the University of Washington.