Unity 2017 Game AI Programming · 3rd Edition by Barrera, Ray -- Read -- Imperial Library of Trantor

Index

Title Page Copyright and Credits

Unity 2017 Game AI Programming Third Edition

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Preface

Who this book is for What this book covers To get the most out of this book

Download the example code files Download the color images Conventions used

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The Basics of AI in Games

Creating the illusion of life Neural Networks Leveling up your game with AI Using AI in Unity Defining the agent Finite State Machines Seeing the world through our agent's eyes Path following and steering

Dijkstra's algorithm Using A* Pathfinding

IDA* Pathfinding

Using Navigation Mesh

Flocking and crowd dynamics Behavior trees Thinking with fuzzy logic Summary

Finite State Machines and You

Finding uses for FSMs Creating state machine behaviors

Creating the AnimationController asset Layers and parameters The animation controller inspector Bringing behaviors into the picture Creating our very first state Transitioning between states

Setting up our player tank Creating the enemy tank

Choosing transitions Making the cogs turn

Setting conditions Driving parameters via code Making our enemy tank move Testing

Summary

Implementing Sensors

Basic sensory systems

Cone of sight Hearing, feeling, and smelling using spheres Expanding AI through omniscience Getting creative with sensing

Setting up the scene Setting up the player tank and aspect

Implementing the player tank Implementing the Aspect class

Creating an AI character Using the Sense class Giving a little perspective Touching is believing Testing the results Summary

Finding Your Way

Following a path

The path script Using the path follower Avoiding obstacles Adding a custom layer Obstacle avoidance

A* Pathfinding

Revisiting the A* algorithm Implementation

The Node class Establishing the priority queue Setting up our grid manager Diving into our A* implementation Implementing a TestCode class Testing it in the sample scene Testing all the components

A* vs IDA*

Navigation mesh

Inspecting our map Navigation Static Baking the navigation mesh Using the NavMesh agent Setting a destination Making sense of Off Mesh Links

Summary

Flocks and Crowds

Learning the origins of flocks Understanding the concepts behind flocks and crowds Using the Reynolds algorithm

Implementing the FlockController The flock target The scene layout

Using crowds

Implementing a simple crowd simulation Using the CrowdAgent component Adding some fun obstacles

Summary

Behavior Trees

Learning the basics of behavior trees

Understanding different node types

Defining composite nodes Understanding decorator nodes Describing the leaf node

Evaluating the existing solutions Implementing a basic behavior tree framework

Implementing a base Node class Extending nodes to selectors Moving on to sequences Implementing a decorator as an inverter Creating a generic action node

Testing our framework

Planning ahead Examining our scene setup Exploring the MathTree code Executing the test

HomeRock card game example

The scene setup The enemy state machine Testing the game

Summary

Using Fuzzy Logic to Make Your AI Seem Alive

Defining fuzzy logic

Picking fuzzy systems over binary systems

Using fuzzy logic

Implementing a simple fuzzy logic system Expanding the sets Defuzzifying the data

Using the resulting crisp data

Using a simpler approach

The morality meter example

The question and answer classes Managing the conversation

Loading up the questions Handling user input Calculating the results

Scene setup Testing the example

Finding other uses for fuzzy logic

Merging with other concepts Creating a truly unique experience

Summary

How It All Comes Together

Setting up the rules Creating the towers

Making the towers shoot

Setting up the tank

Bonus tank abilities

Setting up the environment Testing the example Summary

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