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

Chapter 8. Crowd Interactions

After understanding how to develop an AI character that can move freely around the map, searching for the best paths to arrive at certain destinations, we can start working on the interaction between characters. In this chapter, we will be looking at realistic crowd interactions, how to develop a believable crowd behavior, and how a character should perceive the rest of the group. The goal of this chapter is to keep giving information to our AI character about the environment, and in this particular case, about the other intelligent agents of the game. On this chapter, we will be talking about AI coordination, communication and crowd collision avoidance.