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 explored some popular examples of crowd interaction systems used on popular video games and we saw how important is to plan every interaction that we can think of because this is what will turn a few simple lines of code into a realistic-looking game. To conclude the chapter, we revisited the advanced pathfinding system and we saw how multiple characters in the game can share the same final destination, taking an alternative path to avoid colliding, and waiting in line for other characters to move forward.

In the next chapter, we'll be looking at AI planning and decision making. We'll see how we can have AI anticipating things, knowing in advance what it will do when arriving at a certain position or facing a certain problem.