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


We have explored how to make our AI character create and follow a plan to execute a determinate objective in this chapter. The idea is to think ahead what is going to happen and to prepare for that situation. To complete this, we have also explored how to make our AI character predict a collision with an object or another character. This will be fundamental not only to make our character move freely on the map, but also it serves as a new equation to have in mind when planning what to do. In our next chapter, we will be talking about awareness, how to develop one of the most iconic features of stealth games, and make our AI characters self-aware of what is happening around them with realistic field of view.