Book Image

Practical Game AI Programming

By : Micael DaGraça
Book Image

Practical Game AI Programming

By: Micael DaGraça

Overview of this book

The book starts with the basics examples of AI for different game genres and directly jumps into defining the probabilities and possibilities of the AI character to determine character movement. Next, you’ll learn how AI characters should behave within the environment created. Moving on, you’ll explore how to work with animations. You’ll also plan and create pruning strategies, and create Theta algorithms to find short and realistic looking game paths. Next, you’ll learn how the AI should behave when there is a lot of characters in the same scene. You'll explore which methods and algorithms, such as possibility maps, Forward Chaining Plan, Rete Algorithm, Pruning Strategies, Wall Distances, and Map Preprocess Implementation should be used on different occasions. You’ll discover how to overcome some limitations, and how to deliver a better experience to the player. By the end of the book, you think differently about AI.
Table of Contents (17 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback
Navigation Behavior and Pathfinding
AI Planning and Collision Avoidance


In this chapter, we have introduced point to point movement, a method that is widely used in many games today, and we can adapt the codes that we have created to work in practically any game. At this point ,we are able to re-create many popular games and add our personal touch to them. In the next chapter, we'll continue talking about movement, but we will be focusing on an advanced aspect called the Theta algorithm. This will serve as a continuation of what we have learned in this chapter, and we will be able to create a character AI that, without any previous information or positions, will be able to find for itself the best path to follow in order to arrive at a certain destination.