Description |
xxxiv, 734 pages ; 24 cm + 1 computer optical disc (4 3/4 in.) |
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4 3/4 in |
Series |
AI game programming |
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AI game programming.
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Contents |
Machine derived contents note: Contents -- Preface -- Acknowledgments -- About the Cover Images -- Author Bios -- Section 1 General Wisdom -- 1.1 Custom Tool Design for Game AI -- P.J. Snavely -- 1.2 Using STL and Patterns for Game AI -- James Freeman-Hargis -- 1.3 Declarative AI Design for Games¿Considerations for MMOGs -- Nathan Combs -- 1.4 Designing for Emergence -- Benjamin Wootton -- 1.5 Fun Game AI Design for Beginners -- Matt Gilgenbach -- 1.6 Strategies for Multi-Processor AI -- Sergio Garces -- 1.7 Academic AI Research and Relations with the Game Industry -- Christian Baekkelund -- 1.8 Writing AI as Sport -- Peter Cowling -- Section 2 Pathfinding -- 2.1 Cooperative Pathfinding -- David Silver -- 2.2 Improving on Near-Optimality: More Techniques for Building Navigation Meshes -- Fredrik Farnstrom -- 2.5 Smoothing a Navigation Mesh Path -- Geraint Johnson -- 2.4 Preprocessed Pathfinding Using the GPU -- Renaldas Zioma -- Section 3 Movement -- 3.1 Flow Fields for Movement and Obstacle Avoidance -- Bob Alexander -- 3.2 Autonomous Camera Control with Constraint Satisfaction Methods -- Owen Bourne and Abdul Sattar -- 3.3 Insect AI 2: Implementation Strategies -- Nick Porcino -- 3.4 Intelligent Steering Using Adaptive PID Controllers -- Euan Forrester -- 3.5 Fast, Neat, and Under Control: Arbitrating Between Steering Behaviors -- Heni Ben Amor, Jan Murray, and Oliver Obst -- 3.6 Real-Time Crowd Simulation Using AI.implant -- Paul Kruszewski -- Section 4 Architecture -- 4.1 Flexible Object-Composition Architecture -- Sergio Garces -- 4.2 A Goal-Based, Multi-Tasking Agent Architecture -- Elizabeth Gordon -- 4.3 Orwellian State Machines -- Igor Borovikov -- 4.4 A Flexible AI System through Behavior Compositing -- Matt Gilgenbach and Travis McIntosh -- 4.5 Goal Trees -- Geraint Johnson -- 4.6 A Unified Architecture for Goal Planning and Navigation -- Dominic Filion -- 4.7 Prioritizing Actions in a Goal-Based RTS AI -- Kevin Dill -- 4.8 Extending Simple Weighted-Sum Systems -- Sergio Garces -- 4.9 AI Waterfall: Populating Large Worlds Using Limited Resources -- Sandeep V. Kharkar -- 4.10 An Introduction to Behavior-Based Systems for Games -- Aaron Khoo -- 4.11 Simulating a Plan -- Petar Kotevski -- Section 5 Tactics And Planning -- 5.1 Probabilistic Target Tracking and Search Using Occupancy Maps -- Dami n Isla -- 5.2 Dynamic Tactical Position Evaluation -- Remco Straatman, Arjen Beij, and William van der Sterren -- 5.3 Finding Cover in Dynamic Environments -- Christian J. Darken and Gregory H. Paull -- 5.4 Coordinating Teams of Bots with Hierarchical Task Network Planning -- Hector Munoz-Avila and Hai Hoang -- Section 6 Genre Specific -- 6.1 Training Digital Monsters to Fight in the Real World -- James Boer and John Corpening -- 6.2 The Suffering: Game AI Lessons Learned -- Greg Alt -- 6.3 Environmental Awareness in Game Agents -- Penny Sweetser -- 6.4 Fast and Accurate Gesture Recognition for Character Control -- Markus Wöß -- 6.5 Being a Better Buddy: Interpreting the Player¿s Behavior -- William van der Sterren -- 6.6 Ant Colony Organization for MMORPG and RTS Creature Resource Gathering -- Jason Dunn -- 6.7 RTS Citizen Unit AI -- Shawn Shoemaker -- 6.8 A Combat Flight Simulation AI Framework -- Phil Carlisle -- Section 7 Scripting And Dialog -- 7.1 Opinion Systems -- Adam Russell -- 7.2 An Analysis of Far Cry: Instincts¿ Anchor System -- Eric Martel -- 7.3 Creating a Visual Scripting System -- Matthew McNaughton and Thomas Roy -- 7.4 Intelligent Story Direction in the Interactive Drama Architecture -- Brian Magerko -- Section 8 Learning And Adaptation -- 8.1 Practical Algorithms for In-Game Learning -- John Manslow -- 8.2 A Brief Comparison of Machine Learning Methods -- Christian Baekkelund -- 8.3 Introduction to Hidden Markov Models -- Robert Zubek -- 8.4 Preference-Based Player Modeling -- Jeroen Donkers and Pieter Spronck -- 8.5 Dynamic Scripting -- Pieter Spronck -- 8.6 Encoding Schemes and Fitness Functions for Genetic Algorithms -- Dale Thomas -- 8.7 A New Look at Learning and Games -- Christian Baekkelund -- 8.8 Constructing Adaptive AI Using Knowledge-Based Neuroevolution -- Ryan Cornelius, Kenneth O. Stanley, and Risto Miikkulainen -- About the CD-ROM -- Index |
Summary |
Packed with the insights of industry pros, this book includes tricks, techniques, algorithms, architectures, and approaches to help you avoid redundancy and save useful programming time. This book provides advances, discoveries, and techniques that affects the direction and use of game AI for the next generation of games |
Notes |
Includes index |
Bibliography |
Includes bibliographical references and index |
Notes |
Systems requirements: all code was tested on a Pentium 4.3.0GHz (1GB) machine with an ATI Radeon 9800 graphics card, WinXP with DirectX 9, Microsoft Visual Studio .NET 2003 |
Subject |
Artificial intelligence.
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Computer games -- Design.
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Computer games -- Programming.
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Computer graphics.
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Author |
Rabin, Steve.
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LC no. |
2006003868 |
ISBN |
1584504579 (hardcover with cd-rom : alk. paper) |
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