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

Unreal Navigation System

The Unreal navigation system is based on a Navigation Mesh (Nav Mesh for short). It entails dividing the navigable space into areas in this case, polygons which are subdivided into triangles for efficiency. Then, to reach a certain place, each triangle is considered a node of a graph, and if two triangles are adjacent, then their respective nodes are connected. On this graph, you can execute a pathfinding algorithm, such as A* with a Euclidean distance heuristic, or even something more complicated (e.g. variants of A* or systems that take into consideration different costs). This will produce a path among these triangles where the AI character can walk.

In reality, this process is a little bit more complicated, because considering all the triangles as nodes of a giant graph will produce a good result, but it is inefficient, especially...