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You're reading from  Hands-On Reinforcement Learning with Python

Product typeBook
Published inJun 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781788836524
Edition1st Edition
Languages
Python
Tools
TensorFlowKeras
Concepts
Reinforcement Learning
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Sudharsan Ravichandiran
Sudharsan Ravichandiran
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Sudharsan Ravichandiran

Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
Read more about Sudharsan Ravichandiran

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Chapter 8

  1. Deep Q Network (DQN) is a neural network used for approximating the Q function.
  2. Experience replay is used to remove the correlations between the agent's experience.
  3. When we use the same network for predicting target value and predicted value there will lot of divergence so we use separate target network.
  4. Because of the max operator DQN overestimates Q value.
  5. By having two separate Q functions each learning independently double DQN avoids overestimating Q values.
  6. Experiences are priorities based on TD error in prioritized experience replay.
  7. Dueling DQN estimating the Q value precisely by breaking the Q function computation into value function and advantage function.
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Hands-On Reinforcement Learning with Python
Published in: Jun 2018Publisher: PacktISBN-13: 9781788836524
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Sudharsan Ravichandiran

Sudharsan Ravichandiran is a data scientist and artificial intelligence enthusiast. He holds a Bachelors in Information Technology from Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning including natural language processing and computer vision. He is an open-source contributor and loves answering questions on Stack Overflow.
Read more about Sudharsan Ravichandiran

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