Book Image

Unity Artificial Intelligence Programming - Fourth Edition

By : Dr. Davide Aversa, Aung Sithu Kyaw, Clifford Peters
Book Image

Unity Artificial Intelligence Programming - Fourth Edition

By: Dr. Davide Aversa, Aung Sithu Kyaw, Clifford Peters

Overview of this book

Developing Artificial Intelligence (AI) for game characters in Unity 2018 has never been easier. Unity provides game and app developers with a variety of tools to implement AI, from the basic techniques to cutting-edge machine learning-powered agents. Leveraging these tools via Unity's API or built-in features allows limitless possibilities when it comes to creating your game's worlds and characters. This fourth edition with Unity will help you break down AI into simple concepts to give you a fundamental understanding of the topic to build upon. Using a variety of examples, the book then takes those concepts and walks you through actual implementations designed to highlight key concepts and features related to game AI in Unity. Further on, you'll learn how to distinguish the state machine pattern and implement one of your own. This is followed by learning how to implement a basic sensory system for your AI agent and coupling it with a Finite State Machine (FSM). Next, you'll learn how to use Unity's built-in NavMesh feature and implement your own A* pathfinding system. You'll then learn how to implement simple ?ocks and crowd dynamics, which are key AI concepts in Unity. Moving on, you'll learn how to implement a behavior tree through a game-focused example. Lastly, you'll apply all the concepts in the book to build a popular game.

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Table of Contents (13 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
Introduction to AI
Introduction to AI
Artificial Intelligence (AI)
AI in games
AI techniques
Summary
2
Finite State Machines
Finite State Machines
The player's tank
The Bullet class
Setting up waypoints
The abstract FSM class
The enemy tank AI
Using an FSM framework
Summary
3
Randomness and Probability
Randomness and Probability
Randomness in games
Definitions of probability
Character personalities
FSM with probability
Dynamic AI
Demo slot machine
Summary
Further reading
4
Implementing Sensors
Implementing Sensors
Basic sensory systems
Scene setup
The player's tank and the aspect class
AI characters
Testing
Summary
5
Flocking
Flocking
Basic flocking behavior
Alternative implementation
Summary
6
Path-Following and Steering Behaviors
Path-Following and Steering Behaviors
Following a path
Avoiding obstacles
Summary
7
A* Pathfinding
A* Pathfinding
Revisiting the A* algorithm
Implementing the A* algorithm
Setting up the scene
Testing the pathfinder
Summary
8
Navigation Mesh
Navigation Mesh
Setting up the map
Scene with slope
Navigation areas
Off Mesh Links
Summary
9
Behavior Trees
Behavior Trees
Introduction to Behavior Trees
Implementing a BT in Unity with Behavior Bricks
Summary
External Resources
10
Machine Learning in Unity
Machine Learning in Unity
The Unity Machine Learning Agents Toolkit
How to install the ML-Agents Toolkit
Using the ML-Agents Toolkit – a basic example
Summary
Further reading
11
Putting It All Together
Putting It All Together
Basic game structure
Adding automated navigation
Creating decision-making AI with FSM
Summary
12
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Preface

This book is meant to help you to incorporate various Artificial Intelligence (AI) techniques into your games. We will discuss decision techniques such as Finite State Machines (FSMs) and behavior trees. We will also look at movement, obstacle avoidance, and flocking. We also show how to follow a path, how to create a path using the A* pathfinding algorithm, and then how to reach a destination using a navigation mesh. As a bonus, we will go into detail about randomness and probability, and then incorporate these ideas into a final project.

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