Practical Game AI Programming: Unleash the power of Artificial Intelligence to your game

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Possibility and Probability Maps

In this chapter, we'll be talking about possibility and probability maps, understanding how and where they are used. We'll also be learning the best practices for creating an AI that reacts to the player and that also chooses the best options, as we look to create a character that can make decisions as a human would.

As we saw previously, video games used to rely heavily on predetermining the behavior of what the AI could do in different scenarios that were either created by the game itself or by the player's actions. This method has been present since day one and is still being used today, making it an extremely valuable method for creating quality AI characters. Before explaining, in detail, what each of the maps do, and before demonstrating how to create them in order to develop good AI behavior, it's always good to have...

Key benefits

Move beyond using libraries to create smart game AI, and create your own AI projects from scratch

Implement the latest algorithms for AI development and in-game interaction

Customize your existing game AI and make it better and more efficient to improve your overall game performance

Description

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.

What you will learn

Get to know the basics of how to create different AI for different type of games

Know what to do when something interferes with the AI choices and how the AI should behave if that happens

Plan the interaction between the AI character and the environment using Smart Zones or Triggering Events

Use animations correctly, blending one animation into another and rather than stopping one animation and starting another

Calculate the best options for the AI to move using Pruning Strategies, Wall Distances, Map Preprocess Implementation, and Forced Neighbours

Create Theta algorithms to the AI to find short and realistic looking paths

Add many characters into the same scene and make them behave like a realistic crowd

What do you get with Print?