Learn and Implement game AI in Unity 2018 to build smart game environments and enemies with A*, Finite State Machines, Behavior Trees and NavMesh.
Key Features:
- Build richer games by learning the essential concepts in AI for games like Behavior Trees and Navigation Meshes
- Implement character behaviors and simulations using the Unity Machine Learning toolkit
- Explore the latest Unity 2018 features to make implementation of AI in your game easier
Book Description:
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 flocks 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.
What You Will Learn:
- Create smarter game worlds and characters with C# programming
- Apply automated character movement using pathfinding and steering behaviors
- Implement non-player character decision-making algorithms using Behavior Trees and FSMs
- Build believable and highly efficient artificial flocks and crowds
- Create sensory systems for your AI with the most commonly used techniques
- Construct decision-making systems to make agents take different actions
- Explore the application of machine learning in Unity
Who this book is for:
This book is intended for Unity developers with a basic understanding of C# and the Unity editor. Whether you're looking to build your first game or are looking to expand your knowledge as a game programmer, you will find plenty of exciting information and examples of game AI in terms of concepts and implementation.
Dr. Davide Aversa holds a PhD in artificial intelligence and an MSc in artificial intelligence and robotics from the University of Rome La Sapienza in Italy. He has a strong interest in artificial intelligence for the development of interactive virtual agents and procedural content generation. He served as a Program Committee member of video game-related conferences such as the IEEE conference on computational intelligence and games, and he also regularly participates in game-jam contests. He also writes a blog on game design and game development.
Aung Sithu Kyaw is passionate about graphics programming, creating video games, writing, and sharing knowledge with others. He holds an MSc degree in digital media technology from the Nanyang Technological University (NTU), Singapore. He worked as a research associate, which involved implementing a sensor-based real-time movie system using Unreal Development Kit. In 2011, he founded a tech start-up focusing on interactive media productions and backend server-side technologies.
Clifford Peters is a programmer and a computer scientist. He has reviewed the following Packt Publishing books: Unity Game Development Essentials, Unity 3D Game Development by Example Beginner's Guide, Unity 3 Game Development Hotshot, Unity 3.x Game Development by Example Beginner's Guide, Unity iOS Game Development Beginner's Guide, and Unity iOS Essentials.
