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    Learning Game AI Programming with Lua
    Learning Game AI Programming with Lua
    Learning Game AI Programming with Lua
    Ebook785 pages3 hours

    Learning Game AI Programming with Lua

    By David Young

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    About this ebook

    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.

    LanguageEnglish
    PublisherPackt Publishing
    Release dateNov 28, 2014
    ISBN9781783281343
    Learning Game AI Programming with Lua
    Author

    David Young

    David Young was born in Wellington, New Zealand in 1963. This is his first novel and was drafted during lockdown and whilst on holiday. David currently resides in Auckland with his family.

    Read more from David Young

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      Learning Game AI Programming with Lua - David Young

      Table of Contents

      Learning Game AI Programming with Lua

      Credits

      About the Author

      About the Reviewers

      www.PacktPub.com

      Support files, eBooks, discount offers, and more

      Why subscribe?

      Free access for Packt account holders

      Preface

      What this book covers

      What you need for this book

      Who this book is for

      Conventions

      Reader feedback

      Customer support

      Downloading the example code

      Downloading the color images of this book

      Errata

      Piracy

      Questions

      1. Getting Started with AI Sandbox

      Introduction to AI sandbox

      Understanding the sandbox

      The project layout

      The Premake build

      Compiling the sandbox with Visual Studio 2008/2010/2012/2013

      Open source libraries

      Open source tools

      Lua IDE – Decoda

      Running AI sandbox inside Decoda

      Setting up a new Decoda project

      Debugging Lua scripts

      Decoda Watch window

      Decoda Call Stack window

      The Decoda Virtual Machines window

      Simultaneous Lua and C++ debugging

      Visual Studio – Attach to Process

      Decoda – Attach to Process

      Decoda – Attach System Debugger

      Associating Lua scripts from code with Decoda

      The Lua virtual machine

      The Lua stack

      Lua primitives

      Metatables

      Metamethods

      Userdata

      C/C++ calling Lua functions

      Lua calling C/C++ functions

      Function binding

      Creating custom userdata

      Looking at the vector data type

      The demo framework

      Ogre

      Object-Oriented Input System

      SandboxApplication

      Sandbox

      Agent

      Utility classes

      Lua binding

      Summary

      2. Creating and Moving Agents

      Creating a new sandbox project

      Setting up the file structure

      Extending the SandboxApplication class

      Running your sandbox for the first time

      Creating a new Decoda project

      Configuring Decoda's run executable

      Creating a sandbox Lua script

      Creating a floor

      Adding a light

      Adding a skybox

      Adding meshes to the sandbox

      Creating sandbox objects

      Shooting blocks

      Creating an agent Lua script

      Creating a visual representation

      Updating an agent position

      Updating an agent orientation

      Agent properties

      Orientation

      The forward axis

      The left axis

      The up axis

      Location

      Position

      Size

      Height

      Radius

      Physics

      Mass

      The max force

      The max speed

      Speed

      Velocity

      Knowledge

      Target

      Target radius

      Path

      Agents' movement

      Mass

      Speed

      Velocity

      Acceleration

      Force

      Agent-steering forces

      Seeking

      Applying steering forces to an agent

      Clamping the horizontal speed of an agent

      Creating a seeking agent

      Pursuit

      Fleeing

      Evasion

      Wandering

      The target speed

      Path following

      Creating a path following agent

      Avoidance

      Collision avoidance

      Obstacle avoidance

      Avoiding blocks and agents

      Group steering

      Alignment

      Cohesion

      Separation

      Creating a group of followers

      Summing steering forces

      Weighted sums

      Priority-based forces

      Summary

      3. Character Animations

      Skeletons and meshes

      Mesh skeletons

      Loading an animated mesh

      Showing a skeleton

      Attaching meshes to bones

      Attaching a weapon to our soldier

      Animation clips

      Playing an animation on our soldier

      Soldier animations

      Crouching animations

      Standing animations

      Weapon animations

      Soldier poses

      Weapon poses

      Manipulating animations

      Enabling and disabling animations

      Looping animations

      The animation length

      The animation time

      Normalized time

      Restarting an animation

      Playing a non-looping animation

      The animation rate

      Animation blending

      Animation weights

      Blend window

      Blend curves

      Linear blending

      Playing with blend weights

      Animation state machine (ASM)

      States

      Transitions

      Creating animation state machines

      Creating helper functions

      Adding states

      Adding transitions

      Adding external helper functions

      Forcefully setting states

      Requesting states

      Updating the animation state machine

      Handling state transitions and state requests

      Updating running animations

      Adding functions to animation state machine instances

      Building a weapon animation state machine

      Building a soldier animation state machine

      Updating animation state machines

      Playing with states

      Summary

      4. Mind Body Control

      Creating a body

      Creating a soldier

      Attaching an animated mesh to an agent

      Creating an obstacle course

      Displaying the physics world

      Adding callbacks to the animation state machine

      Handling callbacks

      Adding callbacks to the ASM

      Updating the ASM to call callbacks

      Getting our soldier to shoot

      The bone position

      The bone rotation

      Creating particle effects

      The particle direction

      Object removal

      The collision impact callback

      Shooting a projectile

      Handling projectile collision impacts

      Shooting

      Getting our soldier to run

      Setting a path through the obstacle course

      Running the obstacle course

      Creating a brain

      Approaches for mind body control

      Direct animation control

      The death state

      The idle state

      The falling state

      The moving state

      The shooting state

      A simple, finite state machine

      Initializing the agent

      Agent FSM state handling

      Indirect animation control

      The animation controller

      Commands

      The command queue

      Manipulating commands

      The change stance command

      The die command

      The fall command

      The idle command

      The move command

      The shoot command

      Assigning member functions

      Initializing the controller

      Adding handlers for commands

      Updating the controller

      Running the obstacle course

      Creating a direct control agent

      Creating an indirect control agent

      Indirect control agent initialization

      Indirect control agent update

      Indirect control agent control

      Spawning an indirect control agent

      Action latency

      Summary

      5. Navigation

      Pathfinding

      Creating a navigation mesh

      Configuring navigation meshes

      The walkable height

      The walkable radius

      The walkable climb height

      The walkable slope angle

      The minimum region area

      Building the navigation mesh

      Drawing the navigation mesh

      Pathfinding on a navigation mesh

      Path query

      Query results

      Random navigation points

      The path information

      Adding random pathfinding to our soldier

      Updating agent paths

      Drawing paths

      Initializing the navmesh

      Randomly running agents

      Creating additional navigation meshes

      Summary

      6. Decision Making

      Creating userdata

      Agent actions

      Adding data members

      Initializing an action

      Updating an action

      Action cleanup

      Action member functions

      Creating actions

      The idle action

      The die action

      The reload action

      The shoot action

      The random move action

      The move action

      The flee action

      The pursue action

      Evaluators

      Creating evaluators

      Constant evaluators

      Has ammo evaluator

      Has critical health evaluator

      Has enemy evaluator

      Has move position evaluator

      Is alive evaluator

      Can shoot enemy evaluator

      50/50 chance evaluator

      Decision structures

      Decision trees

      Branches

      Decision leaves

      Branch evaluation

      Building a decision tree

      Creating branches

      Creating a decision tree agent

      Strengths of decision trees

      Pitfalls of decision trees

      Finite state machines

      States

      Transitions

      Finite state machine structure

      Helper functions

      Adding states and transitions

      Updating the finite state machine

      Adding instance functions

      Building a finite state machine

      The idle state

      The movement state

      The random movement state

      The shoot state

      The flee state

      The die state

      The pursue state

      The reload state

      Creating a finite state machine agent

      Strengths of finite state machines

      Pitfalls of finite state machines

      Behavior trees

      The behavior tree node

      Helper functions

      Updating the behavior tree node

      Actions

      Conditions

      Selectors

      Sequences

      Creating a behavior tree object

      Behavior tree helper functions

      Selector evaluation

      Sequence evaluation

      Node evaluation

      Continue behavior tree evaluation

      The behavior tree update loop

      Updating the behavior tree

      Building a behavior tree

      The death behavior

      The flee behavior

      Combat behaviors

      The reload behavior

      The shoot behavior

      The pursue behavior

      The move behavior

      The random move behavior

      The idle behavior

      Creating a behavior tree agent

      Strengths of behavior trees

      Pitfalls of behavior trees

      Summary

      7. Knowledge Representation

      Knowledge sources

      Creating a knowledge source

      Knowledge source evaluation

      Blackboards

      Creating a blackboard

      Adding and removing knowledge sources

      Evaluating knowledge sources

      Setting and retrieving blackboard attributes

      Blackboard member functions

      Creating soldier knowledge sources

      Enemy selection

      Flee position selection

      Constructing a soldier blackboard

      Updating decision evaluators

      Updating behavior actions

      The die action

      The flee action

      The idle action

      The move action

      The pursue action

      The reload action

      The shoot action

      Summary

      8. Perception

      Events

      Attributes

      Sending events

      Receiving events

      Managing events

      Assigning agent teams

      Handling agent communications

      Event types

      Creating agent senses

      Initializing senses

      Updating senses

      Agent visibility

      Detecting other visible agents

      Agent sighting events

      New enemy sighted event

      New dead enemy body sighted event

      New dead teammate body sighted event

      Handling new agent sightings

      Intermittent agent sightings

      Throttling agent visibility updates

      Creating event handlers

      Adding event handlers

      Agent auditory senses

      Auditory events

      The BulletShot event

      The BulletImpact event

      Handling auditory events

      Decaying blackboard events

      Decaying auditory events

      Team communications

      The EnemySelection event

      The PositionUpdate event

      The RetreatPosition event

      Updating agent behaviors

      Enemy selection

      Scoring dangerous positions

      Score danger from bullet impacts

      Score danger from bullet shots

      Score danger from enemies

      Score danger from dead bodies

      Calculating the best flee position

      Summary

      9. Tactics

      Influence maps

      The cell height

      The cell width

      Constructing an influence map

      Configuration

      Voxelizing a navigation mesh

      Drawing influence maps

      Accessing influences

      Setting influences

      Getting influences

      Clearing influences

      Spreading influences

      Cell inertia

      Cell falloff

      Influence map layers

      Updating the influence map

      Soldier tactics

      Initializing and updating tactics

      Scoring team influences

      Initializing team influences

      Updating team influences

      Configuring team influences

      Scoring dangerous areas

      Tapping into agent events

      Adding event handlers

      Initializing dangerous influences

      Updating dangerous influences

      Configuring team influences

      Summary

      Index

      Learning Game AI Programming with Lua

      Learning Game AI Programming with Lua

      Copyright © 2014 Packt Publishing

      All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.

      Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.

      Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.

      First published: November 2014

      Production reference: 1241114

      Published by Packt Publishing Ltd.

      Livery Place

      35 Livery Street

      Birmingham B3 2PB, UK.

      ISBN 978-1-78328-133-6

      www.packtpub.com

      Cover image by Aniket Sawant (<[email protected]>)

      Credits

      Author

      David Young

      Reviewers

      Mitch Allen

      Stanislav Costiuc

      Predrag Končar

      Bayard Randel

      Ross Rothenstine

      Jayant C Varma

      Commissioning Editor

      Aarthi Kumaraswamy

      Acquisition Editor

      Nikhil Karkal

      Content Development Editor

      Mohammed Fahad

      Technical Editor

      Veronica Fernandes

      Copy Editor

      Stuti Srivastava

      Project Coordinator

      Danuta Jones

      Proofreaders

      Paul Hindle

      Julie Jackson

      Clyde Jenkins

      Indexer

      Rekha Nair

      Production Coordinator

      Kyle Albuquerque

      Cover Work

      Kyle Albuquerque

      About the Author

      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.

      I would like to thank my wife; without her support, this book would not have been possible.

      About the Reviewers

      Mitch Allen publishes video games for iOS and Android using Corona SDK and Unity3D. You can find links to his apps at http://mitchallen.com. You can also follow him on Twitter at @mitchallen.

      He has worked on web and mobile projects for Lotus, IBM, the New York Times, Caterpillar Inc., Dragon Systems, Dictaphone, Nuance Communications, Yahoo!, Intuit Inc., and a number of startups.

      He specializes in software development, automated testing, website performance testing, SDK testing, API testing, and technical writing.

      He has served as a technical reviewer for Corona SDK Mobile Game Development Beginner's Guide, Packt Publishing.

      Predrag Končar is a game developer and multimedia researcher. His primary areas of interest are games and combining technology and art. He is also into image and audio processing and interactive design and likes to spend his free time painting. In the last 12 years, he has worked as a technical and creative director for many online projects, published over 40 online games, participated in the production of several iOS apps, and worked with Packt Publishing as a technical reviewer on Corona SDK Mobile Game Development Beginner's Guide and Corona SDK Application Design. He has a strong background in Unity, C#, ActionScript, Lua, MEL script, Maya, and Python. He is a member of MENSA and ACM SIGGRAPH.

      Bayard Randel is a software engineer at Canonical and is working on the Ubuntu Linux infrastructure. He lives in Dunedin, New Zealand. His technical interests include software education with Lua, web development, distributed systems, and functional programming.

      Jayant C Varma is an Australian author, developer, trainer, and consultant with a special focus on mobile development and the use of mobile applications in businesses. He is the author of Learn Lua for iOS Game Development and is in the process of authoring another book for Packt Publishing on Xcode 6, apart from a few other books with other publishers. He is the principal consultant at OZ Apps, which is a company he founded. It specializes in mobile business solutions and development-related services.

      Jayant has been in the IT Industry for quite a while and has seen things change from 8-bit computers and apps on cassette tapes to present-day mobile devices and app stores. He has always been drawn toward new technologies. He has worked in different domains during his career—which have seen him travel to different countries—including as the IT manager for BMW dealerships. He has also helped them set up wireless diagnostics in their workshop and contactless key readers at service receptions, and he has also automated the front office (including sales automation, ordering, prospecting, CRM, and so on in the early 2000s). He has also worked as a lecturer at the James Cook University and a trainer for the Apple University Consortium (AUC) and Australian Computer Society (ACS), among others, actively conducting trainings and workshops. He has created several mobile and desktop applications for clients, which are available on the App Store.

      He has been a reviewer on more than half a dozen books for Packt Publishing. He can be contacted via his website at http://www.oz-apps.com.

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      Preface

      Game AI is a combination of decision making and animation playback. Although classic or academic AI is focused solely on finding the right decision to make, game AI is responsible for acting on numerous decisions over time. Treating game AI independent from animation is a classic mistake that this book avoids by integrating animation and locomotion systems immediately into the AI systems. This subtle difference of decision making and execution changes many of the aspects that game AI programmers have to focus on.

      The other large issue with game AI is regarding the specific needs and implementation strategies that are genre-specific. In order to prevent a watered-down approach, this book focuses on one specific genre, which is the first- and third-person action genre. Limiting the AI to this decision allows for an in-depth, tutorial-based approach of creating a full AI system. The overall goal of this book is to create an AI sandbox composed of professional level C and C++ open source libraries exposed to an AI system scripted in Lua.

      What this book covers

      Chapter 1, Getting Started with AI Sandbox, begins with learning the overview of how projects are set up as well as how the Lua script interacts with C++ code. Here, the beginnings of the AI sandbox are built from open source technologies, starting with a framework that integrates Lua, Ogre3D, OpenSteer, and Bullet Physics.

      Chapter 2, Creating and Moving Agents, starts off with examples of the lowest layer of AI interaction with the world, local steering, and movement. Here, agent seeking, avoiding, and group movement are introduced into the sandbox through the use of the OpenSteer library.

      Chapter 3, Character Animations, continues with the AI sandbox by exposing Ogre3D's animation playback and resource handling of Lua scripts. Low-level structures for controlling animation clips, animation state machines, and layered animations are integrated into the sandbox.

      Chapter 4, Mind Body Control, combines animation handling with local steering and agent movement. Two different approaches toward mind and body interactions will be implemented. The first will focus on the latency between agent decisions and actions, while the second approach will focus on the perceived quality of the agent's actions.

      Chapter 5, Navigation, builds up from local movement and moves on to long distance movement and planning. Navigation mesh generation provided by the Recast library will be integrated into the AI sandbox in order to allow A* pathfinding provided by the Detour library.

      Chapter 6, Decision Making, adds intelligence to the choices the AI agents make. Different data structures and approaches to creating modular and reusable decision logic are covered through Lua scripts. Decision trees, finite state machines, and behavior trees are integrated into the sandbox.

      Chapter 7, Knowledge Representation, adds the ability to store long-term and short-term information for individual agents. A centralized approach to storing and propagating agent knowledge about the world is exposed to Lua.

      Chapter 8, Perception, exposes the services that are available to agents for them to query information about the world. Approaches toward visual- and communication-based information is integrated into the sandbox.

      Chapter 9, Tactics, exposes a high-level spatial knowledge of the environment to the sandbox. Through a grid-based representation of the world, different knowledge sources are combined in order to give you an accurate tactical view of the environment for decision making.

      What you need for this book

      The AI sandbox solution and project files are built automatically through Premake, which is the utility program. Visual Studio 2008, 2010, 2012, and 2013 were tested for compatibility with each of the included demos. With the large number of dependencies the sandbox builds from the source, the project setup is only supported from Visual Studio.

      The open source Lua IDE, which is Decoda, is used to write and debug Lua scripts within the sandbox. While other Lua script editors can be used, the sandbox natively exposes information that allows seamless Lua debugging within Decoda.

      Who this book is for

      This book is aimed at programmers who are looking to understand all the facets involved with the creation of the game AI. You should be comfortable with C or C++ and the Lua programming language. While no direct C or C++ knowledge is required, being able to fully debug into the sandbox allows for extending the existing functionality. A combination of both functional and object-oriented Lua will be used by the sandbox, and both approaches will be explained. Additional understanding of modern game engines will be useful but is not required.

      Conventions

      In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

      Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: The LuaScriptUtilities header defines the metatable name of the vector type.

      A block of code is set as follows:

      local function CallCallbacks(callbacks, stateName, looping)

          for index = 1, #callbacks do

              callbacks[index].callback(

                  stateName, looping, callbacks[index].data);

          end

      end

      New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: Open the Settings menu under the Project menu.

      Note

      Warnings or important notes appear in a box like this.

      Tip

      Tips and tricks appear like this.

      Reader feedback

      Feedback from our readers is always welcome. Let us know what you think about this book—what you liked or disliked. Reader feedback is important for us as it helps us develop titles that you will really get the most out of.

      To send us general feedback, simply e-mail <[email protected]>, and mention the book's title in the subject of your message.

      If there is a topic that you have expertise in and you are interested in either writing or contributing to a book, see our author guide at www.packtpub.com/authors.

      Customer support

      Now that you are the proud owner of a Packt book, we have a number of things to help you to get the most from your purchase.

      Downloading the example code

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      Downloading the color images of this book

      We also provide you with a PDF file that has color images of the screenshots/diagrams used in this book. The color images will help you better understand the changes in the output. You can download this file from: https://www.packtpub.com/sites/default/files/downloads/1336OS_ColoredImages.pdf.

      Errata

      Although we have taken every care to ensure the accuracy of our content, mistakes do happen. If you find a mistake in one of our books—maybe a mistake in the text or the code—we would be grateful if you could report this to us. By doing so, you can save other readers from frustration and help us improve subsequent versions of this book. If you find any errata, please report them by visiting http://www.packtpub.com/submit-errata, selecting your book, clicking on the Errata Submission Form link, and entering the details of your errata. Once your errata are verified, your submission will be accepted and the errata will be uploaded to our website or added to any list of existing errata under the Errata section of that title.

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