Book Image

Unity Artificial Intelligence Programming - Fifth Edition

By : Dr. Davide Aversa
Book Image

Unity Artificial Intelligence Programming - Fifth Edition

By: Dr. Davide Aversa

Overview of this book

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. The updated fifth edition of Unity Artificial Intelligence Programming starts by breaking down AI into simple concepts. 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. As you progress, you’ll learn how to implement a finite state machine (FSM) to determine how your AI behaves, apply probability and randomness to make games less predictable, and implement a basic sensory system. Later, you’ll understand how to set up a game map with a navigation mesh, incorporate movement through techniques such as A* pathfinding, and provide characters with decision-making abilities using behavior trees. By the end of this Unity book, you’ll have the skills you need to bring together all the concepts and practical lessons you’ve learned to build an impressive vehicle battle game.
Table of Contents (17 chapters)
1
Part 1:Basic AI
6
Part 2:Movement and Navigation
11
Part 3:Advanced AI

Testing the learning environment

Before we start learning, we want to test the environment by controlling the Agents with manual input. It is very useful to debug the learning environment without wasting hours of the training process.

Fortunately, the ML-Agents Toolkit makes it very handy to control an agent with live input. We only need two steps:

  1. We add the Heuristic method to the SphereAgent component. This function allows us to manually specify the values of the ActionBuffer objects. In our case, we want to add the two continuous actions to the input axes of the controller:
        public override void Heuristic(
          in ActionBuffers actionsOut) {
            var continuousActionsOut = 
              actionsOut.ContinuousActions;
            continuousActionsOut[0] = 
          ...