Learning Game AI Programming with Lua - Couverture souple

David Young

Couverture souple

ISBN 10 : 1783281332 ISBN 13 : 9781783281336

Editeur : Packt Publishing, 2014

Synopsis

A step-by-step tutorial approach, where new systems and techniques are introduced and implemented by the reader. Each script system builds upon the previous systems adding new functionality to the AI. The AI Sandbox focuses on experimentation and iteration speed to quickly build up AI features.
If you are a game developer or a general programmer who wishes to focus on programming systems and techniques to build your game AI without creating low-level interfaces in a game engine, then this book is for you. Having knowledge of C++ would come in handy to debug the entirety of the AI sandbox and expand on the features present within the book, but it is not required.

A propos du livre

Présentation de l'éditeur

Leverage the power of Lua programming to create game AI that focuses on motion, animation, and tactics

About This Book

• Focus on programming game AI rather than handling low-level resource management
• Bind Lua to build a script-based game AI using a C++ backend that provides hooks for graphics, physics, and resource handling
• A tutorial-based approach where AI functionalities are layered piece by piece to create fully functional AI

Who This Book Is For

If you are a game developer or a general programmer who wishes to focus on programming systems and techniques to build your game AI without creating low-level interfaces in a game engine, then this book is for you.

Knowledge of C++ will come in handy to debug the entirety of the AI sandbox and expand on the features present within the book, but it is not required.

What You Will Learn

• Create an animation state machine to drive AI animations within Lua
• Build and find paths on navigation meshes
• Write and debug Lua scripts within a full-scale Lua IDE
• Develop decision logic with behavior trees, state machines, and decision trees to build modular, reusable AI
• Manage short- and long-term knowledge representation with blackboard data structures
• Add sensory perception to give AIs the ability to see and hear
• Develop high-level tactics with multiple AIs based on influence maps

In Detail

Game AI can be easily broken up into a number of components such as decision making, animation handling, and tactics, but the balance and interaction between each system strikes a balance between good AI and bad AI.

Beginning with an introduction to the AI sandbox, each new aspect of game AI is introduced, implemented, and then expanded upon. Going forward, you will learn to utilize open source libraries such as Ogre3D, Bullet Physics, OpenSteer, Recast, Detour, and Lua to create an AI sandbox with an entire codebase available to expand and step through.

This is done through a step-by-step approach, from learning to move basic shapes to fully animating your soldiers. By the end of the book, your AI will be able to navigate, pathfind, manage animation playback, communicate, and perceive their environment.

Biographie de l'auteur

David Young

David Young is a professional software engineer who works within the game industry. He started his career at NASA's Deep Space Network and later moved to NASA's Jet Propulsion Laboratory for the Curiosity rover mission. After leaving NASA, he worked on the platform that powers Riot Game's League of Legends. David is pursuing a PhD at the University of Southern California, focusing on graphics research in the field of real-time hair rendering and simulation.

Détails de l'édition

• Éditeur: Packt Publishing
• Date d'édition: 2014
• Langue: anglais
• ISBN 10: 1783281332
• ISBN 13: 9781783281336
• Reliure: Broché
• Nombre de pages: 400
• Coordonnées du fabricant: non disponible
• Personne responsable: gpsr@libri.de; gpsr@libri.de; ; Friedensallee 273; Hamburg; 22763; Allemagne