Book Image

Unity Artificial Intelligence Programming - Fourth Edition

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

Unity Artificial Intelligence Programming - Fourth Edition

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

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.
Table of Contents (13 chapters)

Basic flocking behavior

As we said in the introduction to this chapter, we can describe a flocking behavior by using just three intuitive rules:

  • Separation: Also called short-range repulsion, this instructs each boid to maintain a minimum distance with neighboring boids to avoid collisions. You can imagine this rule as a force that pushes the boid away from the others.
  • Alignment: According to this rule, each boid tends to move in the same direction as the flock (measured as the average direction of all the individual boids).
  • Cohesion: Also called long-range attraction, this instructs each boid to move toward the center of mass of the flock (measured by averaging the position of each boid in the flock). You can imagine this rule as a force that pushes the boid toward the center of the flock.

In this section, we'll create our scene with flocks of objects, and will implement...