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)

Creating decision-making AI with FSM

In Chapter 2, Finite State Machines, we saw how to implement a simple FSM. In this section, we are using the same technique, but will apply it to the more complex scenario of this demo.

First of all, we need an FSM plan. For this demo, we are interested only in how to connect the FSM to the existing game, so we will keep it simple. The FSM for our tank is composed of just two states, patrolling and shooting.

The plan is nice and simple:

  • The AI tank starts in the Patrol state, and wanders around the patrolling points we defined before.
  • Then, if the players get in range, the tank switches into the Attack state.
  • In the Attack state, the tank turns toward the player and start shooting at it.
  • Finally, if we are in the Attack state and the players leaves the AI's range, the tank will go back to the Patrol state.

For the implementation, do...