Ai Game Programming Wisdom 2

Rabin, Steve

ISBN 10: 1584502894 / ISBN 13: 9781584502890

Verlag: Cengage Learning, 1754

Beschreibung

No disk. In very good condition with minimal signs of use. The binding is tight and the pages are clean and intact. The cover has minor wear, marks and/or other blemishes. ; 7.5 X 1.75 X 9.25 inches; 600 pages. Bestandsnummer des Verkäufers ZK-W1NB-V8X6

Bibliografische Details

Titel: Ai Game Programming Wisdom 2

Verlag: Cengage Learning

Erscheinungsdatum: 1754

Einband: Hardcover

Zustand: Very Good

Über diesen Titel

Inhaltsangabe:

Presents articles by artificial intelligence programmers that discuss techniques, concepts, architectures, and philosophies of AI game programming.

Críticas:

Preface Acknowledgments About the Cover Images Author Bios SECTION 1 GENERAL WISDOM 1.1 The Evolution of Game AI 1.2 The Illusion of Intelligence 1.3 Solving the Right Problem 1.4 12 Tips from the Trenches SECTION 2 USEFUL TECHNIQUES AND SPECIALIZED SYSTEMS 2.1 Building an AI Diagnostic Toolset 2.2 A General-Purpose Trigger System 2.3 A Data-Driven Architecture for Animation Selection 2.4 Realistic Character Behavior with Prioritized, Categorized Animation 2.5 Designing a GUI Tool to Aid in the Development of Finite-State Machines 2.6 The Beauty of Response Curves 2.7 Simple and Efficient Line-of-Sight for 3D Landscapes 2.8 An Open-Source Fuzzy Logic Library SECTION 3 PATHFINDING WITH A* 3.1 Basic A* Pathfinding Made Simple 3.2 Generic A* Pathfinding 3.3 Pathfinding Design Architecture 3.4 How to Achieve Lightning-Fast A* 3.5 Practical Optimizations for A* Path Generation SECTION 4 PATHFINDING AND MOVEMENT 4.1 Simple, Cheap Pathfinding 4.2 Preprocessed Solution for Open Terrain Navigation 4.3 Building a Near-Optimal Navigation Mesh 4.4 Realistic Turning between Waypoints 4.5 Navigating Doors, Elevators, Ledges, and Other Obstacles 4.6 Simple Swarms as an Alternative to Flocking SECTION 5 TACTICAL ISSUES AND INTELLIGENT GROUP MOVEMENT 5.1 Strategic and Tactical Reasoning with Waypoints 5.2 Recognizing Strategic Dispositions: Engaging the Enemy 5.3 Squad Tactics: Team AI and Emergent Maneuvers 5.4 Squad Tactics: Planned Maneuvers 5.5 Tactical Team AI Using a Command Hierarchy 5.6 Formations SECTION 6 GENERAL PURPOSE ARCHITECTURES 6.1 Architecting a Game AI 6.2 An Efficient AI Architecture Using Prioritized Task Categories 6.3 An Architecture Based on Load Balancing 6.4 A Simple Inference Engine for a Rule-Based Architecture 6.5 Implementing a State Machine Language 6.6 Enhancing a State Machine Language through Messaging SECTION 7 DECISION-MAKING ARCHITECTURES 7.1 Blackboard Architectures 7.2 Introduction to Bayesian Networks and Reasoning Under Uncertainty 7.3 A Rule-Based Architecture Using the Dempster-Shafer Theory 7.4 An Optimized Fuzzy Logic Architecture for Decision-Making 7.5 A Flexible Goal-Based Planning Architecture SECTION 8 FPS, RTS, AND RPG AI 8.1 First-Person Shooter Al Architecture 8.2 Architecting an RTS AI 8.3 An Economic Approach to Goal-Directed Reasoning in an RTS 8.4 The Basics of Ranged Weapon Combat 8.5 Level-Of-Detail AI for a Large Role-Playing Game 8.6 A Dynamic Reputation System Based on Event Knowledge SECTION 9 RACING AND SPORTS AI 9.1 Representing a Racetrack for the AI 9.2 Racing AI Logic 9.3 Training an AI to Race 9.4 Competitive AI Racing under Open Street Conditions 9.5 Camera AI for Replays 9.6 Simulating Real Animal Behavior 9.7 Agent Cooperation in FSMs for Baseball 9.8 Intercepting a Ball SECTION 10 SCRIPTING 10.1 Scripting: Overview and Code Generation 10.2 Scripting: The Interpreter Engine 10.3 Scripting: System Integration 10.4 Creating Scripting Languages for Nonprogrammers 10.5 Scripting for Undefined Circumstances 10.6 The Perils of Al Scripting 10.7 How Not to Implement a Basic Scripting Language SECTION 11 LEARNING 11.1 Learning and Adaptation 11.2 Varieties of Learning 11.3 GoCap: Game Observation Capture 11.4 Pattern Recognition with Sequential Prediction 11.5 Using N-Gram Statistical Models to Predict Player Behavior 11.6 Practical Natural Language Learning 11.7 Testing Undefined Behavior as a Result of Learning 11.8 Imitating Random Variations in Behavior Using a Neural Network 11.9 Genetic Algorithms: Evolving the Perfect Troll 11.10 The Dark Art of Neural Networks About the CD-ROM Index