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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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Questions

  1. What are two alternative algorithms to reinforcement learning for solving sequential decision-making problems?
  2. What are the processes that give birth to new individuals in evolutionary algorithms?
  3. What is the source of inspiration for evolutionary algorithms such as genetic algorithms?
  4. How does CMA-ES evolve evolution strategies?
  5. What's one advantage and one disadvantage of evolution strategies?
  6. What's the trick that's used in the Evolution Strategies as a Scalable Alternative to Reinforcement Learning paper to reduce the variance?

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You have been reading a chapter from
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