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Unity Artificial Intelligence Programming - Fourth Edition

By : Dr. Davide Aversa, Aung Sithu Kyaw, Clifford Peters

4.3 (3)

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Unity Artificial Intelligence Programming

4.3 (3)

By: Dr. Davide Aversa, Aung Sithu Kyaw, Clifford Peters

Buy this Book

Overview of this book

Developing Artificial Intelligence (AI) for game characters in Unity 2018 has never been easier. Unity provides game and app developers with a variety of tools to implement AI, from the 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 your game's worlds and characters. This fourth edition with Unity will help you break down AI 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. Further on, you'll learn how 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'll then learn how to implement simple ?ocks and crowd dynamics, which are key AI concepts in Unity. Moving on, you'll learn how to implement a behavior tree through a game-focused example. Lastly, you'll apply all the concepts in the book to build a popular game.

Preface

Who this book is for

What this book covers

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Free Chapter

Introduction to AI

Artificial Intelligence (AI)

AI in games

AI techniques

Summary

Finite State Machines

The player's tank

The Bullet class

Setting up waypoints

The abstract FSM class

The enemy tank AI

Using an FSM framework

Summary

Randomness and Probability

Randomness in games

Definitions of probability

Character personalities

FSM with probability

Dynamic AI

Demo slot machine

Summary

Implementing the A* algorithm

As a first step, we will implement the preliminary classes that we introduced before, such as the Node class, the GridManager class, and the PriorityQueue class. Then, we will use them in the main AStar class.

Node

The Node class will handle each tile object in our 2D grid and will be, used to represent the maps shown in the Node.cs file:

using UnityEngine; 
using System.Collections; 
using System; 
 
public class Node : IComparable { 
  public float nodeTotalCost; 
  public float estimatedCost; 
  public bool bObstacle; 
  public Node parent; 
  public Vector3 position; 
 
  public Node() { 
    this.estimatedCost = 0.0f; 
    this.nodeTotalCost = 1.0f; 
    this.bObstacle = false; 
    this...

Tech Concepts

Programming languages

Tech Tools