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  • Book Overview & Buying Unity 2017 Game AI Programming - Third Edition
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Unity 2017 Game AI Programming - Third Edition

Unity 2017 Game AI Programming - Third Edition - Third Edition

By : Raymundo Barrera, Aung Sithu Kyaw, Thet Naing Oo
2.8 (4)
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Unity 2017 Game AI Programming - Third Edition

Unity 2017 Game AI Programming - Third Edition

2.8 (4)
By: Raymundo Barrera, Aung Sithu Kyaw, Thet Naing Oo

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 (14 chapters)
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Title Page
Packt Upsell
Contributors
Preface
2
Index

Chapter 4. Finding Your Way

Obstacle avoidance is a simple behavior that allows AI entities to reach a target point. It's important to note that the specific behavior implemented in this chapter is meant to be used for behaviors such as crowd simulation, where the main objective of each agent entity is just to avoid the other agents and reach the target. There's no consideration of what would be the most efficient and shortest path. We'll learn about the A* Pathfinding algorithm in the next section.

In this chapter, we will cover the following topics:

  • Path following and steering
  • A custom A* Pathfinding implementation
  • Unity's built-in NavMesh

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