Book Image

Unity 2017 Game AI Programming - Third Edition - Third Edition

Book Image

Unity 2017 Game AI Programming - Third Edition - Third Edition

Overview of this book

Unity 2017 provides game and app developers with a variety of tools to implement Artificial Intelligence. Leveraging these tools via Unity's API or built-in features allows limitless possibilities when it comes to creating your game's worlds and characters. This third edition with Unity will help you break down Artificial Intelligence into simple concepts to give you a fundamental understanding of the topic to build upon. Using a variety of examples, the book then takes those concepts and walks you through actual implementations designed to highlight key concepts, and features related to game AI in Unity 5. Further on you will learn to distinguish the state machine pattern and implement one of your own. This is followed by learning how to implement a basic sensory system for your AI agent and coupling it with a Finite State Machine (FSM). Next you'll learn how to use Unity's built-in NavMesh feature and implement your own A* pathfinding system. You will then learn how to implement simple flocks and crowd's dynamics, key AI concepts. Moving on, you will learn how to implement a behavior tree through a game-focused example. Lastly, you'll combine fuzzy logic concepts with state machines and apply all the concepts in the book to build a simple tank game.
Table of Contents (10 chapters)

Flocking and crowd dynamics

In nature, we can observe what we refer to as flocking behavior in several species. Flocking simply refers to a group moving in unison. Schools of fish, flocks of sheep, and cicada swarms are fantastic examples of this behavior. Modeling this behavior using manual means, such as animation, can be very time-consuming and is not very dynamic. In Chapter 5, Flocks and Crowds, we'll explore a dynamic and programmatic approach to modeling this behavior in a believable way, using a simple set of rules that will drive the behavior of the group and each individual in a group relative to its surroundings.

Similarly, crowds of humans, be it on foot or in vehicles, can be modeled by representing the entire crowd as an entity rather than trying to model each individual as its own agent. Each individual in the group only really needs to know where the group is heading and what their nearest neighbor is up to in order to function as part of the system.