Book Image

Procedural Content Generation for Unity Game Development

By : Ryan Watkins
Book Image

Procedural Content Generation for Unity Game Development

By: Ryan Watkins

Overview of this book

Procedural Content Generation is a process by which game content is developed using computer algorithms, rather than through the manual efforts of game developers. This book teaches readers how to develop algorithms for procedural generation that they can use in their own games. These concepts are put into practice using C# and Unity is used as the game development engine. This book provides the fundamentals of learning and continued learning using PCG. You'll discover the theory of PCG and the mighty Pseudo Random Number Generator. Random numbers such as die rolls and card drafting provide the chance factor that makes games fun and supplies spontaneity. This book also takes you through the full development of a 2D game. Starting with level generation, you'll learn how PCG can make the game environment for you. You'll move into item generation and learn the different techniques to procedurally create game items. Thereafter, you'll be guided through the more abstract PCG areas such as scaling difficulty to the player and even generating music! The book helps you set up systems within your games where algorithms create computationally generated levels, art assets, quests, stories, characters, and weapons; these can substantially reduce the burden of manually creating every aspect of the game. Finally, you'll get to try out your new PCG skills on 3D terrain generation.
Table of Contents (18 chapters)
Procedural Content Generation for Unity Game Development
Credits
Disclaimer
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

AI


Artificial intelligence, like physics and animation, is also its own field of study. We can use PCG to enhance certain aspects of AI. In Chapter 7, Adaptive Difficulty, we used PCG to rewrite a section of our AI. This isn't always the most practical approach though.

AI for games can be easily visualized as a state machine or a graph of connected behaviors. Some actions in the AI graph might lead to others or some situations might cause an AI to enact a certain behavior. In the following diagram, we see rectangles represented as states and arrows representing states transitioning into other states. This network of states can be as complex or simple as we like.

AI state machine

An example of a complex AI state machine is Bethesda's Radiant AI. This AI system has the NPCs react to the actions of the player, but also has them generate a daily routine. They can go to work, travel, and some might set out to attempt assassinations. These behaviors are programmed separately, but then the routine...