Book Image

Hands-On Artificial Intelligence with Unreal Engine

By : Francesco Sapio
5 (1)
Book Image

Hands-On Artificial Intelligence with Unreal Engine

5 (1)
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)
Free Chapter
1
Section 1: The Unreal Framework
9
Section 2: Designing and Implementing Behavior Trees
13
Section 3: Debugging Methods
14
Debugging Methods for AI - Logging

Summary

In this chapter, we explored how the Environment Querying System can make spatial reasoning in the Decision-Making domain.

In particular, we have understood how the whole system works in general, and then we went through the built-in nodes of the system. We also saw how it is possible to visualize a Query by using a special Pawn. Finally, we explored how it is possible to extend the system.

In the next chapter, we will explore Agent Awareness, and the built-in Sensing system.