Book Image

Unity 2017 Game AI Programming - Third Edition - Third Edition

Book Image

Unity 2017 Game AI Programming - Third Edition - Third Edition

Overview of this book

Unity 2017 provides game and app developers with a variety of tools to implement Artificial Intelligence. 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 third edition with Unity will help you break down Artificial Intelligence 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 5. Further on you will learn 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 will then learn how to implement simple flocks and crowd's dynamics, key AI concepts. Moving on, you will learn how to implement a behavior tree through a game-focused example. Lastly, you'll combine fuzzy logic concepts with state machines and apply all the concepts in the book to build a simple tank game.
Table of Contents (10 chapters)

Summary

I'm glad to see that you've made it to the end of the chapter. Fuzzy logic tends to become far less fuzzy once you understand the basic concepts. Being one of the more pure math concepts in the book, it can be a little daunting if you're not familiar with the lingo, but when presented in a familiar context, the mystery fades away, and you're left with a very powerful tool to use in your game.

We learned how fuzzy logic is used in the real world, and how it can help illustrate vague concepts in a way that binary systems cannot. We also learned how to implement our own fuzzy logic controllers using the concepts of member functions, degrees of membership, and fuzzy sets. In addition to this, we also played around with a faction/morality system to further illustrate the concept of fuzzy logic in the context of a choose-your-own-adventure-style interaction...