Book Image

Unity 2018 Artificial Intelligence Cookbook - Second Edition

By : Jorge Palacios
Book Image

Unity 2018 Artificial Intelligence Cookbook - Second Edition

By: Jorge Palacios

Overview of this book

Interactive and engaging games come with intelligent enemies, and this intellectual behavior is combined with a variety of techniques collectively referred to as Artificial Intelligence. Exploring Unity's API, or its built-in features, allows limitless possibilities when it comes to creating your game's worlds and characters. This cookbook covers both essential and niche techniques to help you take your AI programming to the next level. To start with, you’ll quickly run through the essential building blocks of working with an agent, programming movement, and navigation in a game environment, followed by improving your agent's decision-making and coordination mechanisms – all through hands-on examples using easily customizable techniques. You’ll then discover how to emulate the vision and hearing capabilities of your agent for natural and humanlike AI behavior, and later improve the agents with the help of graphs. This book also covers the new navigational mesh with improved AI and pathfinding tools introduced in the Unity 2018 update. You’ll empower your AI with decision-making functions by programming simple board games, such as tic-tac-toe and checkers, and orchestrate agent coordination to get your AIs working together as one. By the end of this book, you’ll have gained expertise in AI programming and developed creative and interactive games.
Table of Contents (12 chapters)

Using N-Grams for content generation

In Chapter 8, Learning Techniques, we learned how N-Grams is a probabilistic language model for predicting the next item in a sequence of n-1 elements, and how it can be applied in learning techniques for predicting player behavior. However, it can also be used for procedural content generation—creating new elements by imitating the style of a given set.

In this recipe, we will use the power of N-Grams for creating new levels from a given set, thus imitating the style of the designer.

Getting ready

It's important to remind ourselves about the N-Gram predictor that we developed in Chapter 8, Learning Techniques, as we will use it as a tool for building levels based on the previous...