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Home > Game Development > Game Artificial Intelligence > Unity 5.x Game AI Programming Cookbook
Unity 5.x Game AI Programming Cookbook
Unity 5.x Game AI Programming Cookbook

Unity 5.x Game AI Programming Cookbook: Build and customize a wide range of powerful Unity AI systems with over 70 hands-on recipes and techniques

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Unity 5.x Game AI Programming Cookbook

Chapter 2. Navigation

In this chapter, we will cover the following recipes:

  • Representing the world with grids
  • Representing the world with Dirichlet domains
  • Representing the world with points of visibility
  • Representing the world with a self-made navigation mesh
  • Finding your way out of a maze with DFS
  • Finding the shortest path in a grid with BFS
  • Finding the shortest path with Dijkstra
  • Finding the best-promising path with A*
  • Improving A* for memory: IDA*
  • Planning navigation in several frames: time-sliced search
  • Smoothing a path

Introduction

In this chapter, we will learn path-finding algorithms for navigating complex scenarios. Game worlds are usually complex structures; whether a maze, an open world, or everything in between. That's why we need different techniques for approaching these kinds of problems.

We'll learn some ways of representing the world using different kinds of graph structures, and several algorithms for finding a path, each aimed at different situations.

It is worth mentioning that path-finding algorithms rely on techniques such as Seek and Arrive, learnt in the previous chapter, in order to navigate the map.

Representing the world with grids

A grid is the most used structure for representing worlds in games because it is easy to implement and visualize. However, we will lay the foundations for advanced graph representations while learning the basis of graph theory and properties.

Getting ready

First, we need to create an abstract class called Graph, declaring the virtual methods that every graph representation implements. It is done this way because, no matter how the vertices and edges are represented internally, the path-finding algorithms remain high-level, thus avoiding the implementation of the algorithms for each type of graph representation.

This class works as a parent class for the different representations to be learned in the chapter and it's a good starting point if you want to implement graph representations not covered in the book.

The following is the code for the Graph class:

  1. Create the backbone with the member values:
    using UnityEngine;
using System.Collections;
using System...

Representing the world with Dirichlet domains

Also called a Voronoi polygon, a Dirichlet domain is a way of dividing space into regions consisting of a set of points closer to a given seed point than to any other. This graph representation helps in distributing the space using Unity's primitives or existing meshes, thus not really adhering to the definition, but using the concept as a means to an end. Dirichlet domains are usually mapped using cones for delimiting the area of a given vertex, but we're adapting that principle to our specific needs and tool.

Representing the world with Dirichlet domains

Example of a Voronoi Diagram or Voronoi Polygon

Getting ready

Before building our new Graph class, it's important to create the VertexReport class, make some modifications to our Graph class, and add the Vertex tag in the project:

  1. Prepend the VertexReport class to the Graph class specification, in the same file:
    public class VertexReport
{
    public int vertex;
    public GameObject obj;
    public VertexReport(int vertexId...

Representing the world with points of visibility

This is another widely-used technique for world representation based on points located throughout the valid area of navigation, whether manually placed or automated via scripting. We'll be using manually-placed points connected automatically via scripting.

Getting ready

Just like the previous representation, it's important to have several things in order before continuing:

  • Having the Edge class prepended to the Graph class in the same file
  • Defining the GetEdges function in the Graph class
  • Having the Vertex class

Note

The vertex objects in the scene must have a collider component attached to them, as well as the Vertex tag assigned. It's recommended for them to be unitary Sphere primitives.

How to do it...

We'll be creating the graph representation class as well as a custom Vertex class:

  1. Create the VertexVisibility class deriving from Vertex:
    using UnityEngine;
using System.Collections.Generic;

public class VertexVisibility : Vertex...

Representing the world with a self-made navigation mesh

Sometimes, a custom navigation mesh is necessary for dealing with difficult situations such as different types of graphs, but placing the graph's vertices manually is troublesome because it requires a lot of time to cover large areas.

We will learn how to use a model's mesh in order to generate a navigation mesh based on its triangles' centroids as vertices, and then leverage the heavy lifting from the previous recipe we learned.

Getting ready

This recipe requires some knowledge of custom editor scripting and understanding and implementing the points of visibility in the graph representation. Also, it is worth mentioning that the script instantiates a CustomNavMesh game object automatically in the scene and requires a prefab assigned, just like any other graph representation.

Finally, it's important to create the following class, deriving from GraphVisibility:

using UnityEngine;
using System.Collections;
using System...

Finding your way out of a maze with DFS

The Depth-First Search (DFS) algorithm is a path-finding technique suitable for low-memory devices. Another common use is to build mazes with a few modifications to the list of nodes visited and discovered, however the main algorithm stays the same.

Getting ready

This is a high-level algorithm that relies on each graph's implementation of the general functions, so the algorithm is implemented in the Graph class.

It is important to

How to do it...

Even though this recipe is only defining a function, please take into consideration the comments in the code to understand the indentation and code flow for effectively:

  1. Declare the GetPathDFS function:
    public List<Vertex> GetPathDFS(GameObject srcObj, GameObject dstObj)
{
    // next steps
}
  2. Validate if input objects are null:
    if (srcObj == null || dstObj == null)
    return new List<Vertex>();
  3. Declare and initialize the variables we need for the algorithm:
    Vertex src = GetNearestVertex(srcObj.transform...

Introduction

In this chapter, we will learn path-finding algorithms for navigating complex scenarios. Game worlds are usually complex structures; whether a maze, an open world, or everything in between. That's why we need different techniques for approaching these kinds of problems.

We'll learn some ways of representing the world using different kinds of graph structures, and several algorithms for finding a path, each aimed at different situations.

It is worth mentioning that path-finding algorithms rely on techniques such as Seek and Arrive, learnt in the previous chapter, in order to navigate the map.

Representing the world with grids

A grid is the most used structure for representing worlds in games because it is easy to implement and visualize. However, we will lay the foundations for advanced graph representations while learning the basis of graph theory and properties.

Getting ready

First, we need to create an abstract class called Graph, declaring the virtual methods that every graph representation implements. It is done this way because, no matter how the vertices and edges are represented internally, the path-finding algorithms remain high-level, thus avoiding the implementation of the algorithms for each type of graph representation.

This class works as a parent class for the different representations to be learned in the chapter and it's a good starting point if you want to implement graph representations not covered in the book.

The following is the code for the Graph class:

  1. Create the backbone with the member values:

    using UnityEngine;
using System.Collections;
using System.Collections...

Representing the world with Dirichlet domains

Also called a Voronoi polygon, a Dirichlet domain is a way of dividing space into regions consisting of a set of points closer to a given seed point than to any other. This graph representation helps in distributing the space using Unity's primitives or existing meshes, thus not really adhering to the definition, but using the concept as a means to an end. Dirichlet domains are usually mapped using cones for delimiting the area of a given vertex, but we're adapting that principle to our specific needs and tool.

Example of a Voronoi Diagram or Voronoi Polygon

Getting ready

Before building our new Graph class, it's important to create the VertexReport class, make some modifications to our Graph class, and add the Vertex tag in the project:

  1. Prepend the VertexReport class to the Graph class specification, in the same file:

    public class VertexReport
{
    public int vertex;
    public GameObject obj;
    public VertexReport(int vertexId, GameObject obj...

Representing the world with points of visibility

This is another widely-used technique for world representation based on points located throughout the valid area of navigation, whether manually placed or automated via scripting. We'll be using manually-placed points connected automatically via scripting.

Getting ready

Just like the previous representation, it's important to have several things in order before continuing:

  • Having the Edge class prepended to the Graph class in the same file

  • Defining the GetEdges function in the Graph class

  • Having the Vertex class

Note

The vertex objects in the scene must have a collider component attached to them, as well as the Vertex tag assigned. It's recommended for them to be unitary Sphere primitives.

How to do it...

We'll be creating the graph representation class as well as a custom Vertex class:

  1. Create the VertexVisibility class deriving from Vertex:

    using UnityEngine;
using System.Collections.Generic;

public class VertexVisibility : Vertex
{
    void Awake...

Representing the world with a self-made navigation mesh

Sometimes, a custom navigation mesh is necessary for dealing with difficult situations such as different types of graphs, but placing the graph's vertices manually is troublesome because it requires a lot of time to cover large areas.

We will learn how to use a model's mesh in order to generate a navigation mesh based on its triangles' centroids as vertices, and then leverage the heavy lifting from the previous recipe we learned.

Getting ready

This recipe requires some knowledge of custom editor scripting and understanding and implementing the points of visibility in the graph representation. Also, it is worth mentioning that the script instantiates a CustomNavMesh game object automatically in the scene and requires a prefab assigned, just like any other graph representation.

Finally, it's important to create the following class, deriving from GraphVisibility:

using UnityEngine;
using System.Collections;
using System.Collections.Generic...

Finding your way out of a maze with DFS

The Depth-First Search (DFS) algorithm is a path-finding technique suitable for low-memory devices. Another common use is to build mazes with a few modifications to the list of nodes visited and discovered, however the main algorithm stays the same.

Getting ready

This is a high-level algorithm that relies on each graph's implementation of the general functions, so the algorithm is implemented in the Graph class.

It is important to

How to do it...

Even though this recipe is only defining a function, please take into consideration the comments in the code to understand the indentation and code flow for effectively:

  1. Declare the GetPathDFS function:

    public List<Vertex> GetPathDFS(GameObject srcObj, GameObject dstObj)
{
    // next steps
}

  2. Validate if input objects are null:

    if (srcObj == null || dstObj == null)
    return new List<Vertex>();

  3. Declare and initialize the variables we need for the algorithm:

    Vertex src = GetNearestVertex(srcObj.transform...
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Key benefits

  • *Empower your agent with decision making capabilities using advanced minimaxing and Negamaxing techniques
  • Discover how AI can be applied to a wide range of games to make them more interactive.
  • *Instigate vision and hearing abilities in your agent through collider based and graph based systems

Description

Unity 5 comes fully packaged with a toolbox of powerful features to help game and app developers create and implement powerful game AI. 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 practical Cookbook covers both essential and niche techniques to help you be able to do that and more. This Cookbook is engineered as your one-stop reference to take your game AI programming to the next level. Get to grips with the essential building blocks of working with an agent, programming movement and navigation in a game environment, and improving your agent's decision making and coordination mechanisms - all through hands-on examples using easily customizable techniques. Discover how to emulate vision and hearing capabilities for your agent, for natural and humanlike AI behaviour, and improve them with the help of graphs. Empower your AI with decision-making functions through programming simple board games such as Tic-Tac-Toe and Checkers, and orchestrate agent coordination to get your AIs working together as one.

Who is this book for?

This book is intended for those who already have a basic knowledge of Unity and are eager to get more tools under their belt to solve AI and gameplay-related problems.

What you will learn

  • * Use techniques such as A*and A*mbush to empower your agents with path finding capabilities.
  • * Create a representation of the world and make agents navigate it
  • * Construct decision-making systems to make the agents take different actions
  • * Make different agents coordinate actions and create the illusion of technical behavior
  • * Simulate senses and apply them in an awareness system
  • * Design and implement AI in board games such as Tic-Tac-Toe and Checkers
  • * Implement efficient prediction mechanism in your agents with algorithms such as N-Gram predictor and naïve Bayes classifier
  • * Understand and analyze how the influence maps work.

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Last updated date : Feb 11, 2025
Publication date : Mar 31, 2016
Length: 278 pages
Edition : 1st
Language : English
ISBN-13 : 9781783553587
Vendor :
Unity Technologies
Category :
Game Development
Concepts :
Game Artificial Intelligence
Tools :
Unity

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want
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Product Details

Last updated date : Feb 11, 2025
Publication date : Mar 31, 2016
Length: 278 pages
Edition : 1st
Language : English
ISBN-13 : 9781783553587
Vendor :
Unity Technologies
Category :
Game Development
Concepts :
Game Artificial Intelligence
Tools :
Unity

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Table of Contents

9 Chapters
1. Behaviors – Intelligent Movement Chevron down icon Chevron up icon
1. Behaviors – Intelligent Movement
Introduction
Creating the behavior template
Pursuing and evading
Arriving and leaving
Facing objects
Wandering around
Following a path
Avoiding agents
Avoiding walls
Blending behaviors by weight
Blending behaviors by priority
Combining behaviors using a steering pipeline
Shooting a projectile
Predicting a projectile's landing spot
Targeting a projectile
Creating a jump system
2. Navigation Chevron down icon Chevron up icon
2. Navigation
Introduction
Representing the world with grids
Representing the world with Dirichlet domains
Representing the world with points of visibility
Representing the world with a self-made navigation mesh
Finding your way out of a maze with DFS
Finding the shortest path in a grid with BFS
Finding the shortest path with Dijkstra
Finding the best-promising path with A*
Improving A* for memory: IDA*
Planning navigation in several frames: time-sliced search
Smoothing a path
3. Decision Making Chevron down icon Chevron up icon
3. Decision Making
Introduction
Choosing through a decision tree
Working a finite-state machine
Improving FSMs: hierarchical finite-state machines
Combining FSMs and decision trees
Implementing behavior trees
Working with fuzzy logic
Representing states with numerical values: Markov system
Making decisions with goal-oriented behaviors
4. Coordination and Tactics Chevron down icon Chevron up icon
4. Coordination and Tactics
Introduction
Handling formations
Extending A* for coordination: A*mbush
Creating good waypoints
Analyzing waypoints by height
Analyzing waypoints by cover and visibility
Exemplifying waypoints for decision making
Influence maps
Improving influence with map flooding
Improving influence with convolution filters
Building a fighting circle
5. Agent Awareness Chevron down icon Chevron up icon
5. Agent Awareness
Introduction
The seeing function using a collider-based system
The hearing function using a collider-based system
The smelling function using a collider-based system
The seeing function using a graph-based system
The hearing function using a graph-based system
The smelling function using a graph-based system
Creating awareness in a stealth game
6. Board Games AI Chevron down icon Chevron up icon
6. Board Games AI
Introduction
Working with the game-tree class
Introducing Minimax
Negamaxing
AB Negamaxing
Negascouting
Implementing a tic-tac-toe rival
Implementing a checkers rival
7. Learning Techniques Chevron down icon Chevron up icon
7. Learning Techniques
.Introduction
Predicting actions with an N-Gram predictor
Improving the predictor: Hierarchical N-Gram
Learning to use Naïve Bayes classifiers
Learning to use decision trees
Learning to use reinforcement
Learning to use artificial neural networks
Creating emergent particles using a harmony search
8. Miscellaneous Chevron down icon Chevron up icon
8. Miscellaneous
Introduction
Handling random numbers better
Building an air-hockey rival
Devising a table-football competitor
Creating mazes procedurally
Implementing a self-driving car
Managing race difficulty using a rubber-banding system
Index Chevron down icon Chevron up icon
Index

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About the authors

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Profile icon Jorge Palacios
Jorge Palacios
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Jorge Palacios is a software and game developer with a BS in computer science and eight years of professional experience. He's been developing games for the last five years in different roles, from tool developer to lead programmer. Mainly focused on artificial intelligence and gameplay programming, he is currently working with Unity and HTML5. He's also a game-programming instructor, speaker, and game-jam organizer.
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Profile icon Jorge Elieser P Garrido
Jorge Elieser P Garrido
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How do I buy and download an eBook? Chevron down icon Chevron up icon

Where there is an eBook version of a title available, you can buy it from the book details for that title. Add either the standalone eBook or the eBook and print book bundle to your shopping cart. Your eBook will show in your cart as a product on its own. After completing checkout and payment in the normal way, you will receive your receipt on the screen containing a link to a personalised PDF download file. This link will remain active for 30 days. You can download backup copies of the file by logging in to your account at any time.

If you already have Adobe reader installed, then clicking on the link will download and open the PDF file directly. If you don't, then save the PDF file on your machine and download the Reader to view it.

Please Note: Packt eBooks are non-returnable and non-refundable.

Packt eBook and Licensing When you buy an eBook from Packt Publishing, completing your purchase means you accept the terms of our licence agreement. Please read the full text of the agreement. In it we have tried to balance the need for the ebook to be usable for you the reader with our needs to protect the rights of us as Publishers and of our authors. In summary, the agreement says:

  • You may make copies of your eBook for your own use onto any machine
  • You may not pass copies of the eBook on to anyone else
How can I make a purchase on your website? Chevron down icon Chevron up icon

If you want to purchase a video course, eBook or Bundle (Print+eBook) please follow below steps:

  1. Register on our website using your email address and the password.
  2. Search for the title by name or ISBN using the search option.
  3. Select the title you want to purchase.
  4. Choose the format you wish to purchase the title in; if you order the Print Book, you get a free eBook copy of the same title. 
  5. Proceed with the checkout process (payment to be made using Credit Card, Debit Cart, or PayPal)
Where can I access support around an eBook? Chevron down icon Chevron up icon
  • If you experience a problem with using or installing Adobe Reader, the contact Adobe directly.
  • To view the errata for the book, see www.packtpub.com/support and view the pages for the title you have.
  • To view your account details or to download a new copy of the book go to www.packtpub.com/account
  • To contact us directly if a problem is not resolved, use www.packtpub.com/contact-us
What eBook formats do Packt support? Chevron down icon Chevron up icon

Our eBooks are currently available in a variety of formats such as PDF and ePubs. In the future, this may well change with trends and development in technology, but please note that our PDFs are not Adobe eBook Reader format, which has greater restrictions on security.

You will need to use Adobe Reader v9 or later in order to read Packt's PDF eBooks.

What are the benefits of eBooks? Chevron down icon Chevron up icon
  • You can get the information you need immediately
  • You can easily take them with you on a laptop
  • You can download them an unlimited number of times
  • You can print them out
  • They are copy-paste enabled
  • They are searchable
  • There is no password protection
  • They are lower price than print
  • They save resources and space
What is an eBook? Chevron down icon Chevron up icon

Packt eBooks are a complete electronic version of the print edition, available in PDF and ePub formats. Every piece of content down to the page numbering is the same. Because we save the costs of printing and shipping the book to you, we are able to offer eBooks at a lower cost than print editions.

When you have purchased an eBook, simply login to your account and click on the link in Your Download Area. We recommend you saving the file to your hard drive before opening it.

For optimal viewing of our eBooks, we recommend you download and install the free Adobe Reader version 9.

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