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)

Summary

Game AI and academic AI have different objectives. Academic AI researchers try to solve real-world problems and develop AI algorithms that have to compete with human intelligence with the ultimate goal of replacing humans in complex situations. Game AI focuses on building NPCs with limited resources that seem to be intelligent to the player with the ultimate goal of entertaining the players. The objective of AI in games is to provide a challenging opponent that makes the game more fun to play. We also learned briefly about the widely used different AI techniques in games, such as FSMs, random and probability, sensor and input system, flocking and group behaviors, path following and steering behaviors, AI pathfinding, navigation mesh generation, and behavior trees. We'll see how to implement these techniques inside the Unity engine in the following chapters. In the next chapter, we will start from the very basic: Finite State Machines.