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Unity Artificial Intelligence Programming

Unity Artificial Intelligence Programming

By : Dr. Davide Aversa , Aung Sithu Kyaw, Peters
4.3 (3)
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Unity Artificial Intelligence Programming

Unity Artificial Intelligence Programming

4.3 (3)
By: Dr. Davide Aversa , Aung Sithu Kyaw, 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)
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Summary

In this chapter, we learned how to implement flocking behaviors in two ways. First, we examined and learned how to implement a basic flocking algorithm using nothing other than our scripts. Next, we implemented the same algorithm using Unity's Rigidbody component to control the boid's movement and Sphere Collider to avoid collision with other boids.

In our example, we always referred to boids as bird-like entities. However, we can use flocking for a lot of other applications: fishes swimming in the sea, sheep grazing on a plane, a swarm of insects, and even groups of people walking on the street can show a flocking behavior. To adapt the algorithm to different scenarios, we just need to change the values of the flocking rules, and eventually, lock the movement to a plane.

In the next chapter, we, go beyond random movement and take a look at how to follow a specific...

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