Unity Artificial Intelligence Programming : Add Powerful, Believable, and Fun AI Entities in Your Game with the Power of Unity / Davide Aversa.

Format:

Book

Author/Creator:

Aversa, Davide, author.

Language:

English

Subjects (All):

Video games--Development.

Video games.

Video games--Programming.

Physical Description:

1 online resource (309 pages)

Edition:

5th ed.

Distribution:

London : Bloomsbury Publishing (UK), 2024.

Place of Publication:

Birmingham : Packt Publishing, 2022.

System Details:

Mode of access: World Wide Web.

text file HTML

Biography/History:

Davide Aversa Dr. : Dr. Davide Aversa holds a PhD in Artificial Intelligence (AI) and an MSc in AI and robotics from the University of Rome La Sapienza in Italy. He has a strong interest in AI for the development of interactive virtual agents and procedural content generation. He has served as a program committee member for video game-related conferences such as the IEEE conference on computational intelligence and games, and he also regularly participates in game-jam contests. He also writes a blog on game design and game development.

Summary:

Developing artificial intelligence (AI) for game characters in Unity has never been easier. Unity provides game and app developers with a variety of tools to implement AI, from basic techniques to cutting-edge machine learning-powered agents. Leveraging these tools via Unity's API or built-in features allows limitless possibilities when it comes to creating game worlds and characters.

Contents:

Cover

Title

Copyright and Credits

Table of Contents

Part 1: Basic AI

Chapter 1: Introduction to AI

Understanding AI

AI in video games

AI techniques for video games

Finite state machines

Randomness and probability in AI

The sensor system

Flocking, swarming, and herding

Path following and steering

A* pathfinding

Navigation meshes

Behavior trees

Locomotion

Summary

Chapter 2: Finite State Machines

Technical requirements

Implementing the player's tank

Initializing the Tank object

Shooting the bullet

Controlling the tank

Implementing a Bullet class

Setting up waypoints

Creating the abstract FSM class

Using a simple FSM for the enemy tank AI

The Patrol state

The Chase state

The Attack state

The Dead state

Taking damage

Using an FSM framework

The AdvancedFSM class

The FSMState class

The state classes

The NPCTankController class

Chapter 3: Randomness and Probability

Introducing randomness in Unity

Randomness in computer science

The Unity Random class

A simple random dice game

Learning the basics of probability

Independent and correlated events

Conditional probability

Loaded dice

Exploring more examples of probability in games

Character personalities

Perceived randomness

FSM with probability

Dynamically adapting AI skills

Creating a slot machine

A random slot machine

Weighted probability

A near miss

Further reading

Chapter 4: Implementing Sensors

Basic sensory systems

Scene setup

The player's tank and the aspect class

The player's tank

Aspect

AI characters

Sense

Sight

Touch

Testing

Part 2: Movement and Navigation

Chapter 5: Flocking

Technical requirements.

Basic flocking behavior

Individual behavior

Controller

Alternative implementation

FlockController

Chapter 6: Path Following and Steering Behaviors

Chapter 7: A* Pathfinding

Revisiting the A* algorithm

Implementing the A* algorithm

Node

PriorityQueue

The GridManager class

The AStar class

The TestCode class

Setting up the scene

Testing the pathfinder

Chapter 8: Navigation Mesh

Setting up the map

Navigation static

Baking the NavMesh

NavMesh agent

Updating an agent's destinations

Setting up a scene with slopes

Baking navigation areas with different costs

Using Off Mesh Links to connect gaps between areas

Generated Off Mesh Links

Manual Off Mesh Links

Part 3: Advanced AI

Chapter 9: Behavior Trees

Introduction to BTs

A simple example - a patrolling robot

Implementing a BT in Unity with Behavior Bricks

Set up the scene

Implement a day/night cycle

Design the enemy behavior

Implementing the nodes

Building the tree

Attach the BT to the enemy

Chapter 10: Procedural Content Generation

Understanding Procedural Content Generation in games

Kinds of Procedural Content Generation

Implementing a simple goblin name generator

Generating goblin names

Completing the goblin description

Learning how to use Perlin noise

Built-in Unity Perlin noise

Generating random maps and caves

Cellular automata

Implementing a cave generator

Rendering the generated cave

Chapter 11: Machine Learning in Unity

The Unity Machine Learning Agents Toolkit

Installing the ML-Agents Toolkit.

Installing Python and PyTorch on Windows

Installing Python and PyTorch on macOS and Unix-like systems

Using the ML-Agents Toolkit - a basic example

Creating the scene

Implementing the code

Adding the final touches

Testing the learning environment

Training an agent

Chapter 12: Putting It All Together

Developing the basic game structure

Adding automated navigation

Creating the NavMesh

Setting up the agent

Fixing the GameManager script

Creating decision-making AI with FSM

Index.

Notes:

Includes index.

Includes bibliographical references and index.

ISBN:

9781523151462

1523151463

9781803245218

1803245212

OCLC:

1308985626