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Alongside the D4RL datasets, it could be useful to have a pixel-based continuous control benchmark for offline RL integrated into this codebase. One such existing benchmark is V-D4RL with associated TMLR paper: Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations. This would naturally compliment the low-dimensional D4RL datasets and the proposed discrete action space Atari datasets.
I think this would be appropriate for the"call for contributions" stack. @vmoens
Motivation
Alongside the D4RL datasets, it could be useful to have a pixel-based continuous control benchmark for offline RL integrated into this codebase. One such existing benchmark is V-D4RL with associated TMLR paper: Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations. This would naturally compliment the low-dimensional D4RL datasets and the proposed discrete action space Atari datasets.
I think this would be appropriate for the"call for contributions" stack. @vmoens
Solution
Integrate V-D4RL datasets from https://github.com/conglu1997/v-d4rl into
pytorch/rl
Checklist
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