What is recorded here?
Designed datasets spanning narrow support, non-RL controllers, heterogeneous behavior quality and multitask trajectories, with diagnostic navigation and robotic-control tasks for evaluating offline learners.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
Original v1 is titled Datasets for Data-Driven Reinforcement Learning and describes v0 datasets; later D4RL revisions or Minari are not silently substituted. Does not invent the underlying simulators or offline RL; benchmark success is not demonstrated real-world safety or broad deployment.
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People and systems
Justin Fu; Aviral Kumar; Ofir Nachum; George Tucker; Sergey Levine
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
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English catalogue narrative
D4RL: diagnostic datasets and tasks for offline reinforcement learning
Designed datasets spanning narrow support, non-RL controllers, heterogeneous behavior quality and multitask trajectories, with diagnostic navigation and robotic-control tasks for evaluating offline learners.
Scientific scope
Original v1 is titled Datasets for Data-Driven Reinforcement Learning and describes v0 datasets; later D4RL revisions or Minari are not silently substituted. Does not invent the underlying simulators or offline RL; benchmark success is not demonstrated real-world safety or broad deployment.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Justin Fu; Aviral Kumar; Ofir Nachum; George Tucker; Sergey Levine
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.