AI Game Programming Wisdom 3, 1st Edition

  • Steve Rabin
  • ISBN-10: 1584504579  |  ISBN-13: 9781584504573
  • 734 Pages
  • © 2006 | Published
  • List Price = $ 69.95
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AI Game Programming Wisdom 3 grants you an insider's look at cutting-edge AI techniques used by industry professionals in such games as Fable, Halo 2, and the Battlefield series. Successful commercial games like these require years of research and development in order to deliver exciting, new gameplay experiences. The wealth of knowledge gained through this hard work is invaluable and by sharing it, the 50+ authors in this book have generously given you the tools and techniques you need to build top tier games. In AI Game Programming Wisdom 3, you'll find an entirely new collection of exclusive tips, tricks, techniques, algorithms, and architectures that can't be found anywhere else. And as with previous volumes, the goal of this book is to offer useful, insightful, and clever ideas to help expand your own personal AI toolbox. New to this volume is the inclusion of longer and more detailed articles that allow for a more in-depth exploration of each topic. With this book, you'll be standing on the shoulders of game industry giants and taking advantage of their hard earned wisdom and insights. So take these techniques, build upon them, and lead the industry toward innovative gameplay and the next generation of games.

Features and Benefits

  • Topics Covered Include: Learning and AdaptationPathfinding Tactics and PlanningGeneral Wisdom ArchitectureScripting and Dialog MovementGenre Specific
  • ON THE CD-ROM (WIN/LINUX): Source code and demos that demonstrate the techniques described in the book, along with bonus code and documents of interest to game AI programmers.
  • SYSTEM REQUIREMENTS: All code was tested on a Pentium 4 3.0GHz (1GB) machine with an ATI Radeon 9800 graphics card, WinXP with DirectX 9, and Microsoft Visual Studio .NET 2003.

Table of Contents

About the Cover Image
Contributor Bios
1.1 Custom Tool Design for Game AI; 1.2 Using STL and Patterns for Game AI; 1.3 Declarative AI Design for Games—Considerations for MMOGs; 1.4 Designing for Emergence; 1.5 Fun Game AI Design for Beginners; 1.6 Strategies for Multiprocessor AI; 1.7 Academic AI Research and Relations with the Game Industry; 1.8 Writing AI as Sport
2.1 Cooperative Pathfinding; 2.2 Improving on Near-Optimality: More Techniques for Building Navigation Meshes; 2.3 Smoothing a Navigation Mesh Path; 2.4 Preprocessed Pathfinding Using the GPU
3.1 Flow Fields for Movement and Obstacle Avoidance; 3.2 Autonomous Camera Control with Constraint Satisfaction Methods; 3.3 Insect AI 2: Implementation Strategies; 3.4 Intelligent Steering Using Adaptive PID Controllers; 3.5 Fast, Neat, and Under Control: Arbitrating Between Steering Behaviors; 3.6 Real-Time Crowd Simulation Using AI.implant;
4.1 Flexible Object-Composition Architecture; 4.2 A Goal-Based, Multitasking Agent Architecture; 4.3 Orwellian State Machines; 4.4 A Flexible AI System through Behavior Compositing; 4.5 Goal Trees; 4.6 A Unified Architecture for Goal Planning and Navigation; 4.7 Prioritizing Actions in a Goal-Based RTS AI; 4.8 Extending Simple Weighted-Sum Systems; 4.9 AI Waterfall: Populating Large Worlds Using Limited Resources; 4.10 An Introduction to Behavior-Based Systems for Games; 4.11 Simulating a Plan
5.1 Probabilistic Target Tracking and Search Using Occupancy Maps; 5.2 Dynamic Tactical Position Evaluation; 5.3 Finding Cover in Dynamic Environments; 5.4 Coordinating Teams of Bots with Hierarchical Task Network Planning
6.1 Training Digital Monsters to Fight in the Real World; 6.2 The Suffering: Game AI Lessons Learned; 6.3 Environmental Awareness in Game Agents; 6.4 Fast and Accurate Gesture Recognition for Character Control; 6.5 Being a Better Buddy: Interpreting the Player’s Behavior; 6.6 Ant Colony Organization for MMORPG and RTS Creature Resource Gathering; 6.7 RTS Citizen Unit AI; 6.8 A Combat Flight Simulation AI Framework
7.1 Opinion Systems; 7.2 An Analysis of Far Cry Instincts’ Anchor System; 7.3 Creating a Visual Scripting System; 7.4 Intelligent Story Direction in the Interactive Drama Architecture
8.1 Practical Algorithms for In-Game Learning; 8.2 A Brief Comparison of Machine Learning Methods; 8.3 Introduction to Hidden Markov Models; 8.4 Preference-Based Player Modeling; 8.5 Dynamic Scripting; 8.6 Encoding Schemes and Fitness Functions for Genetic Algorithms; 8.7 A New Look at Learning and Games; 8.8 Constructing Adaptive AI Using Knowledge-Based Neuroevolution
About the CD-ROM

Meet the Author

Author Bio

Steve Rabin

Steve Rabin is a Principal Software Engineer at Nintendo of America, where he researches new techniques for Nintendo's next generation systems, develops tools, and supports Nintendo developers. Before Nintendo, Steve worked primarily as an AI engineer at several Seattle start-ups including Gas Powered Games,WizBang Software Productions, and Surreal Software. He managed and edited the AI Game Programming Wisdom series of books, as well as the book Introduction to Game Development, and has over a dozen articles published in the Game Programming Gems series. He's spoken at the Game Developers Conference and moderates the AI roundtables. Steve teaches artificial intelligence at both the University of Washington Extension and at the DigiPen Institute of Technology. He earned a B.S. in computer engineering and an M.S. in computer science, both from the University of Washington.