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

A* search algorithm

Unpredictable situations usually lead to a large amount of hours coding the extensive possibilities that the characters have. For this reason, it was necessary to think on a new way to create a better pathfinding system, where the characters could analyze the surroundings for themselves in real time and choose the best path to take. One method that has become very popular for this effect is using theta algorithms, which allows the characters to constantly search for the best path without it being necessary to manually set which points they need to follow.

The Theta search algorithm (A*) is a widely used search algorithm that can be used to find solutions for many problems and pathfinding is one of them. Using this algorithm to solve pathfinding problems is very common due to the uniform-cost search and heuristic search. The Theta search algorithm examines every corner of the map to help the character determine if it is possible to use that location or not, while trying...