RL Unplugged is suite of benchmarks for offline reinforcement learning. The RL Unplugged is designed around the following considerations: to facilitate ease of use, the datasets are provided with a unified API which makes it easy for the practitioner to work with all data in the suite once a general pipeline has been established. This is a dataset accompanying the paper RL Unplugged: Benchmarks for Offline Reinforcement Learning.

In this suite of benchmarks, the authors try to focus on the following problems:

  • High dimensional action spaces, for example the locomotion humanoid domains, there are 56 dimensional actions.
  • High dimensional observations.
  • Partial observability, observations have egocentric vision.
  • Difficulty of exploration, using states of the art algorithms and imitation to generate data for difficult environments.
  • Real world challenges.
Source: DeepMind


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