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You're reading from  Reinforcement Learning Algorithms with Python

Product typeBook
Published inOct 2019
Reading LevelBeginner
PublisherPackt
ISBN-139781789131116
Edition1st Edition
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Author (1)
Andrea Lonza
Andrea Lonza
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Andrea Lonza

Andrea Lonza is a deep learning engineer with a great passion for artificial intelligence and a desire to create machines that act intelligently. He has acquired expert knowledge in reinforcement learning, natural language processing, and computer vision through academic and industrial machine learning projects. He has also participated in several Kaggle competitions, achieving high results. He is always looking for compelling challenges and loves to prove himself.
Read more about Andrea Lonza

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Best practices of deep RL

Throughout this book, we covered plenty of reinforcement learning algorithms, some of which are only upgrades (for example TD3, A2C, and so on), while others were fundamentally different from the others (such as TRPO and DPG) and propose an alternative way to reach the same objective. Moreover, we addressed non-RL optimization algorithms such as imitation learning and evolution strategies to solve sequential decision-making tasks. All of these alternatives may have created confusion and you may not know exactly which algorithm is best for a particular problem. If that is the case, don't worry, as we'll now go through some rules that you can use in order to decide which is the best algorithm to use for a given task.

Also, if you implemented some of the algorithms we went through in this book, you might find it hard to put all the pieces together...

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Reinforcement Learning Algorithms with Python
Published in: Oct 2019Publisher: PacktISBN-13: 9781789131116

Author (1)

author image
Andrea Lonza

Andrea Lonza is a deep learning engineer with a great passion for artificial intelligence and a desire to create machines that act intelligently. He has acquired expert knowledge in reinforcement learning, natural language processing, and computer vision through academic and industrial machine learning projects. He has also participated in several Kaggle competitions, achieving high results. He is always looking for compelling challenges and loves to prove himself.
Read more about Andrea Lonza