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Learn Unity ML-Agents ??? Fundamentals of Unity Machine Learning

You're reading from   Learn Unity ML-Agents ??? Fundamentals of Unity Machine Learning Incorporate new powerful ML algorithms such as Deep Reinforcement Learning for games

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781789138139
Length 204 pages
Edition 1st Edition
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Author (1):
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Micheal Lanham Micheal Lanham
Author Profile Icon Micheal Lanham
Micheal Lanham
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Q-Learning and connected agents

Typically, Q-Learning is taught using a grid problem such as the one we looked at it in the previous section. Here, though, we want something a little more complex and abstract that also allows you, the reader, to build on it and explore it further. We have put together an interesting example where we represent our bandits as rooms or objects with a number of exit options. This example could also very easily represent a dungeon or another connected room structure that you need to navigate an agent through. Follow these steps to get started on building the connected agents exercise:

  1. From the menu, select Assets -> Import Package -> Custom Package..., then navigate to the book's downloaded source code and import the Chapter_2_Connected_Bandits_unitypackage. This is the example, which has been fully constructed already for you. Apologies...
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Learn Unity ML-Agents ??? Fundamentals of Unity Machine Learning
Published in: Jun 2018
Publisher: Packt
ISBN-13: 9781789138139
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