Farama-Foundation/D4RL

• mediumreadme#1

  Clarify D4RL's current role in the README's introduction

  Why:

  CURRENT

  ## Important Notice
  
  ### All of online environments libraries in D4RL have been moved Gymnasium, MiniGrid and Gymnasium-Robotics, and all offline datasets in DR4L have been moved to Minari. These new versions include large bug fixes, new versions of Python, and are where all new development will continue. Please upgrade these libraries as soon as you're able to do so. If you'd like to read more about the story behind this switch, please check out this blog post.
  
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  </p>
  
  D4RL is an open-source benchmark for offline reinforcement learning. It provides standardized environments and datasets for training and benchmarking algorithms. A supplementary whitepaper and website are also available.

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  Farama-Foundation/D4RL serves as a foundational open-source benchmark for offline reinforcement learning, providing standardized environments and datasets crucial for reproducing prior research. While its active development has transitioned to Gymnasium and Minari, D4RL remains the definitive source for its original datasets.
  
  ## Important Notice
  
  ### All of online environments libraries in D4RL have been moved Gymnasium, MiniGrid and Gymnasium-Robotics, and all offline datasets in DR4L have been moved to Minari. These new versions include large bug fixes, new versions of Python, and are where all new development will continue. Please upgrade these libraries as soon as you're able to do so. If you'd like to read more about the story behind this switch, please check out this blog post.
  
  <p align="center">
      
  </p>
  
  D4RL is an open-source benchmark for offline reinforcement learning. It provides standardized environments and datasets for training and benchmarking algorithms. A supplementary whitepaper and website are also available.

  OpenDoneDismiss
• lowabout#2

  Refine the repository description

  Why:

  CURRENT

  A collection of reference environments for offline reinforcement learning

  COPY-PASTE FIX

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  Foundational benchmark for offline reinforcement learning, providing standardized environments and datasets.

  OpenDoneDismiss

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

• CATEGORY QUERY

  Where can I find standardized datasets and environments for offline reinforcement learning research?

  you: #1
  AI recommended (in order):

  1. D4RL ← you
  2. OpenAI Gym/Farama Foundation Gymnasium
  3. RL Unplugged
  4. Meta-World
  5. RoboStack
  6. CARLA Simulator
  Show full AI answer
• CATEGORY QUERY

  What are good benchmark environments and datasets for evaluating offline RL algorithms?

  you: #1
  AI recommended (in order):

  1. D4RL ← you
  2. OpenAI Gym
  3. Farama Gymnasium
  4. RL Unplugged
  5. DeepMind Control Suite
  6. Meta-World
  7. MiniGrid
  8. RoboNet
  9. Google's Robotic Datasets
  Show full AI answer

• Metadata completeness

  warn

  Suggestion:

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of Farama-Foundation/D4RL?

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• If a team adopts Farama-Foundation/D4RL in production, what risks or prerequisites should they evaluate first?

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• In one sentence, what problem does the repo Farama-Foundation/D4RL solve, and who is the primary audience?

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  ✓AI named Farama-Foundation/D4RL explicitly

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