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 revisited how to create point-to-point movement, but instead of using a simple method, we have studied how huge and successful game studios manage to solve one of the most complicated features of a AI, pathfinding. Here, we have learned how to use theta algorithms to recreate an human feature that helps us search and move in the right direction in order to arrive at the desired destination.

In the next chapter, we will be talking about realistic crowd interactions, a very important aspect when trying to make an AI character as realistic as possible. We will be studying different approaches used in different types of game, and also we will be looking at how humans and animals interact in their environments and how we can use that in our AI code.