Undocumented versions of Meta-World have clouded algorithmic performance. This work strives to disambiguate Meta-World results from the literature, while also providing insights into benchmark design.

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)