wwxFromTju/awesome-reinforcement-learning-zh

• hightopics#1

  Add relevant topics to the repository

  Why:

  CURRENT

  (none)

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  ["reinforcement-learning", "deep-reinforcement-learning", "awesome-list", "chinese", "education", "machine-learning"]

  OpenDoneDismiss
• highreadme#2

  Reposition the README H1 to explicitly state 'Awesome List' and 'Chinese'

  Why:

  CURRENT

  # 强化学习从入门到放弃的资料

  COPY-PASTE FIX

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  # Awesome Reinforcement Learning Resources (Chinese) / 强化学习中文资料精选

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• highlicense#3

  Create a LICENSE file

  Why:

  CURRENT

  (no LICENSE file detected)

  COPY-PASTE FIX

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  Create a LICENSE file (e.g., MIT License) in the repository root to clearly state the terms of use for the list and its contents.

  OpenDoneDismiss

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• CATEGORY QUERY

  I need a curated list of resources to learn reinforcement learning from scratch.

  you: not recommended
  AI recommended (in order):

  1. Reinforcement Learning: An Introduction (Sutton and Barto)
  2. Deep Reinforcement Learning (David Silver's Course at UCL)
  3. spinningup (OpenAI)
  4. Practical Reinforcement Learning (Coursera by HSE and National Research University Higher School of Economics)
  5. RL Course by Google DeepMind (Léon Bottou)
  6. Hands-On Reinforcement Learning with Python (Sudharsan Ravichandiran)
  7. Deep Reinforcement Learning Hands-On (Maxim Lapan)

  AI recommended 7 alternatives but never named wwxFromTju/awesome-reinforcement-learning-zh. This is the gap to close.

  Show full AI answer
• CATEGORY QUERY

  Where can I find updated deep reinforcement learning course materials, possibly in Chinese?

  you: not recommended
  AI recommended (in order):

  1. Deep Reinforcement Learning by David Silver (UCL Course)
  2. Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto
  3. Stanford CS234: Reinforcement Learning by Emma Brunskill
  4. Deep Reinforcement Learning by Sergey Levine (UC Berkeley CS285)
  5. 动手学强化学习 (Dive into Reinforcement Learning) by李沐 (Mu Li) et al.
  6. 强化学习 (Reinforcement Learning) by 莫烦 (Mo Fan)
  7. 强化学习 (Reinforcement Learning) by 蒋尚达 (Shang-Da Jiang)

  AI recommended 7 alternatives but never named wwxFromTju/awesome-reinforcement-learning-zh. This is the gap to close.

  Show full AI answer

• Metadata completeness

  fail

  Suggestion:

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of wwxFromTju/awesome-reinforcement-learning-zh?

  pass
  ⚠AI did not name wwxFromTju/awesome-reinforcement-learning-zh — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• If a team adopts wwxFromTju/awesome-reinforcement-learning-zh in production, what risks or prerequisites should they evaluate first?

  pass
  ⚠AI did not name wwxFromTju/awesome-reinforcement-learning-zh — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• In one sentence, what problem does the repo wwxFromTju/awesome-reinforcement-learning-zh solve, and who is the primary audience?

  pass
  ⚠AI did not name wwxFromTju/awesome-reinforcement-learning-zh — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?