When we think about artificial intelligence, a lot of topics may come to mind. From simple behaviors such as following or escaping from the player, through the classical Chess-rival AI, to state-of-the-art techniques in Machine Learning or procedural content generation.
Talking about Unity means talking about game development democratization. Thanks to its ease of use, fast-paced technological improvement, an ever-growing community of developers, and the new cloud services offered, Unity has become one of the most important game industry software.
With all that in mind, the main goal in writing this book is to offer you, the reader, both technical insight into Unity, following best practices and conventions, and theoretical knowledge that help you grasp artificial intelligence concepts and techniques, so you could get the best of both worlds for your own personal and professional development.
This cookbook will introduce you to the tools to build great AI; either for creating better enemies, polishing that final boss, or even building your own customized AI engine. It aims to be your one-stop reference for developing artificial intelligence techniques in Unity.
Welcome to an exciting journey that combines a variety of things that means a lot to me as a professional and human being; programming, game development, artificial intelligence, and sharing knowledge with other developers. I cannot stress how humbled and happy I am to be read by you right now, and grateful to the team at Packt for this formidable opportunity. I hope this material helps you not only take your Unity and artificial intelligence skills to new levels, but also deliver that feature that will engage players into your game.
Chapter 1, Behaviors – Intelligent Movement, explores some of the most interesting movement algorithms based on the steering behavior principles developed by Craig Reynolds along with work from Ian Millington. They act as a foundation for most of the AI used in advanced games and other algorithms that rely on movement, such as the family of path-finding algorithms.
Chapter 2, Navigation, explores path-finding algorithms for navigating complex scenarios. It will include some ways to represent the world using different kinds of graph structures, and several algorithms for finding a path, each aimed at different situations.
Chapter 3, Decision Making, shows the different decision-making techniques that are flexible enough to adapt to different types of games, and robust enough to let us build modular decision-making systems.
Chapter 4, Coordination and Tactics, deals with a number of different recipes for coordinating different agents as a whole organism, such as formations and techniques that allow us make tactical decisions based on graphs, such as waypoints and influence maps.
Chapter 5, Agent Awareness, deals with different approaches of simulating sense stimuli on an agent. We will learn how to use tools that we already know to create these simulations, colliders, and graphs.
Chapter 6, Board Games AI, explains a family of algorithms for developing board-game techniques to create artificial intelligence.
Chapter 7, Learning Techniques, explores the field of machine learning. It will give us a great head start in our endeavor to learn and apply machine-learning techniques to our games.
Chapter 8, Miscellaneous, introduces new techniques and uses algorithms that we have learned about in previous chapters in order to create new behaviors that don't quite fit in a definite category.