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
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
6
Navigation Behavior and Pathfinding
9
AI Planning and Collision Avoidance

Chapter 9. AI Planning and Collision Avoidance

In this chapter, we will cover topics that will help bring a higher complexity level to our AI characters. The idea of this chapter is to give the power of planning and deciding to the characters. We have already explored some of the technical knowledge required to achieve this in the previous chapters, and now we will explore in detail the process of creating an AI character that can plan ahead their decisions.