Answers.Body: <p>Two books that really helped me to understand RL/deep RL are:</p>
  <p><em><strong>Reinforcement Learning: An Introduction</strong></em> by Andrew Barto and Richard S. Sutton</p>
  <p><em><strong>Deep Reinforcement Learning: Fundamentals, Research and Applications</strong></em> by Hao Dong, Zihan Ding, Shanghang Zhang</p>
  <p>Before, I started getting familiar with RL through online courses and papers, but after even coding and research, I read Sutton's book again and found it really great. It deserves to be the reference for RL. Start with it, and you can see how it improves your vision of RL.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-07-12T14:32:34.167Z
Answers.Text: to piggyback onto this answer, I'd also recommend doing some probability/statistics. Enough so you're familiar with (conditional) probability distributions, expectations, etc.
Answers.UserDisplayName: David
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Answers.CreationDate: 2022-07-12T14:55:47.323Z
Answers.Text: The both are RL books but I am asking for math books.
Answers.UserDisplayName: hanugm
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Answers.CreationDate: 2022-07-12T15:11:52.887Z
Answers.Text: This doesn't answer the question, as mentioned by the OP above. The question is **not**: which RL books do you recommend? Of course, some RL books may contain 1-2 sections on math prerequisites, but that wasn't the question.
Answers.UserDisplayName: nbro
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Answers.CreationDate: 2022-07-12T20:38:51.940Z
Answers.Text: in my opinion both books are enough for getting involve into RL world.
Answers.UserDisplayName: Pouyan
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Answers.CreationDate: 2022-07-12T14:29:25.330Z
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Answers.UserDisplayName: Pouyan
Body: <p>This question is not about the math prerequisites of reinforcement learning, but about the textbooks of mathematics that are enough to understand the literature on reinforcement learning.</p>
  <p>What are the <strong>mathematics books</strong> that are recommended to study in order to understand the majority of the reinforcement learning literature?</p>
  
Tags: <reinforcement-learning><math><resource-request><books>
Title: Mathematics books for reinforcement learning
UserDisplayName: hanugm
ThreadText: # Mathematics books for reinforcement learning
  
  (Asked by: username_0 on 2022-07-12)
  
  This question is not about the math prerequisites of reinforcement learning, but about the textbooks of mathematics that are enough to understand the literature on reinforcement learning.
  
  What are the **mathematics books** that are recommended to study in order to understand the majority of the reinforcement learning literature?
  
  **Tags:** reinforcement-learning, math, resource-request, books
  
  
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  ## 1 answers
  
  ### Answer by username_1 on 2022-07-12. Score: 2
  
  Two books that really helped me to understand RL/deep RL are:
  
  ***Reinforcement Learning: An Introduction*** by Andrew Barto and Richard S. Sutton
  
  ***Deep Reinforcement Learning: Fundamentals, Research and Applications*** by Hao Dong, Zihan Ding, Shanghang Zhang
  
  Before, I started getting familiar with RL through online courses and papers, but after even coding and research, I read Sutton's book again and found it really great. It deserves to be the reference for RL. Start with it, and you can see how it improves your vision of RL.
  
  > **Comments:**
  > **username_2**: to piggyback onto this answer, I'd also recommend doing some probability/statistics. Enough so you're familiar with (conditional) probability distributions, expectations, etc.  
  > **username_0**: The both are RL books but I am asking for math books.  
  > **username_3**: This doesn't answer the question, as mentioned by the OP above. The question is **not**: which RL books do you recommend? Of course, some RL books may contain 1-2 sections on math prerequisites, but that wasn't the question.  
  > **username_1**: in my opinion both books are enough for getting involve into RL world.  
  
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