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  • Hands-On Artificial Intelligence with Unreal Engine
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Hands-On Artificial Intelligence with Unreal Engine

Hands-On Artificial Intelligence with Unreal Engine

By : Francesco Sapio
3 (4)
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Hands-On Artificial Intelligence with Unreal Engine

Hands-On Artificial Intelligence with Unreal Engine

3 (4)
By: Francesco Sapio

Overview of this book

Learning how to apply artificial intelligence ( AI ) is crucial and can take the fun factor to the next level, whether you're developing a traditional, educational, or any other kind of game. If you want to use AI to extend the life of your games and make them challenging and more interesting, this book is for you. The book starts by breaking down AI into simple concepts to get a fundamental understanding of it. Using a variety of examples, you will work through actual implementations designed to highlight key concepts and features related to game AI in UE4. You will learn to work through the built-in AI framework in order to build believable characters for every game genre (including RPG, Strategic, Platform, FPS, Simulation, Arcade, and Educational). You will learn to configure the Navigation, Environmental Querying, and Perception systems for your AI agents and couple these with Behavior Trees, all accompanied with practical examples. You will also explore how the engine handles dynamic crowds. In the concluding chapters, you will learn how to profile, visualize, and debug your AI systems to correct the AI logic and increase performance. By the end of the book, your AI knowledge of the built-in AI system in Unreal will be deep and comprehensive, allowing you to build powerful AI agents within your projects.
Table of Contents (19 chapters)
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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
Section 1: The Unreal Framework
Section 1: The Unreal Framework
2
Making the First Steps in the World of AI
Making the First Steps in the World of AI
Before starting...
Prerequisites
Installing and preparing the software
Becoming an AI Game Developer
A bit of history
Planning our journey
Summary
3
Behavior Trees and Blackboards
Behavior Trees and Blackboards
How Behavior Trees work
Blackboards and their integration with Behavior Trees
Creating our AI project
Starting Behavior Trees from AI Controllers
Summary
4
Navigation
Navigation
What to expect from a Navigation System
Unreal Navigation System
Generating the Navigation Mesh
Setting parameters for the Nav Mesh
Modifying the Navigation Mesh
Overriding the Navigation System
Summary
5
Environment Querying System
Environment Querying System
Enabling the Environment Querying System
Understanding the Environment Querying System
Exploring the built-in nodes
Visualizing Environment Queries
Creating components for the Environment Querying System
Summary
6
Agent Awareness
Agent Awareness
Perception of AI in video games
Overview of the Sensing System
The AIPerceptionComponent
Different Teams
The AIStimuliSourceComponent
Hands-on with the perception system – Sight AI Controller
Summary
7
Extending Behavior Trees
Extending Behavior Trees
A quick recap on Behavior Trees
Creating a Task
Creating a Decorator
Creating a Service
Creating a Composite Node
Creating new type of nodes or new types of Trees
Summary
8
Crowds
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Crowds
Crowds in games
Crowds in Unreal
Reciprocal Velocity Obstacles (RVO)
Detour Crowd
Summary
9
Section 2: Designing and Implementing Behavior Trees
Section 2: Designing and Implementing Behavior Trees
10
Designing Behavior Trees - Part I
Designing Behavior Trees - Part I
The Expected Behavior
Building the Nodes
AI Controller
Summary
11
Designing Behavior Trees - Part II
Designing Behavior Trees - Part II
Setting up the environment for testing the Behavior Tree
Service – Update Chasing Behavior
Summary
12
Designing Behavior Trees - Part III
Designing Behavior Trees - Part III
Building the Behavior Tree
Running the Behavior Tree
Bug Correction
Improving further (C++ only)
Summary
13
Section 3: Debugging Methods
Section 3: Debugging Methods
14
Debugging Methods for AI - Logging
Debugging Methods for AI - Logging
Basic Logging
Summary
15
Debugging Methods for AI - Navigation, EQS, and Profiling
Debugging Methods for AI - Navigation, EQS, and Profiling
Debugging behavior trees
Profiling and visualizing environmental queries
Testing and visualizing the navigation mesh
Profiling AI
Summary
16
Debugging Methods for AI - The Gameplay Debugger
Debugging Methods for AI - The Gameplay Debugger
The anatomy of the Gameplay Debugger
Extending the Gameplay Debugger
Summary
17
Going Beyond
Going Beyond
Why is psychology an important consideration for AI?
What we haven't covered in this book
Some useful resources
AI and philosophy
Goodbye
18
Other Books You May Enjoy
Other Books You May Enjoy
Leave a review - let other readers know what you think

Summary

In this chapter, we have seen how the Unreal Engine handles crowds. In particular, we have seen two built-in systems. The first one is called Reciprocal Velocity Obstacles (RVO), which is very fast, but not very precise. The second is the Detour Crowd, which is a bit more expensive, but more precise and realistic.

In the next chapter, we will move on and learn how to implement our own Behavior Tree from scratch.

End of Chapter 8
Next Chapter
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