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Unity Artificial Intelligence Programming

Unity Artificial Intelligence Programming

By : Dr. Davide Aversa
4.8 (4)
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Unity Artificial Intelligence Programming

Unity Artificial Intelligence Programming

4.8 (4)
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)
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1
Part 1:Basic AI
6
Part 2:Movement and Navigation
11
Part 3:Advanced AI

Chapter 11: Machine Learning in Unity

Machine learning is the hottest buzzword in Artificial Intelligence (AI). Nowadays, everything contains (or claims to contain) some machine learning-powered AI that is supposed to improve our life: calendars, to-do apps, photo management software, every smartphone, and much more. However, even if the phrase machine learning is just a marketing gimmick most of the time, it is without question that machine learning has improved significantly in recent years. Most importantly, though, there are now plenty of tools that allow everybody to implement a learning algorithm without any previous academic-level AI knowledge.

At the moment, machine learning is not used in game development (except for applications for procedural content generation). There are many reasons for that. The main reason, though, is that a designer can't control the output of a machine learning agent, and in game design, uncontrollable outcomes often correlate to not-fun games...

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