How to train environments whose “RL Library” is empty in the Comprehensive List?

Hi, I need some help. In Isaac Lab’s “Available Environments” → “Comprehensive List of Environments,” most environments list a corresponding RL Library and can be trained with commands like:

./isaaclab.sh -p scripts/reinforcement_learning/rsl_rl/train.py --task=Isaac-Lift-Cube-Franka-v0 --headless

and then visualized with play.py.

However, some environments show an empty “RL Library” field, for example Isaac-Stack-Cube-UR10-Long-Suction-IK-Rel-v0. How are these environments supposed to be trained? Are they not yet supported or still under construction by the team? If there’s a recommended workflow or example script for these, could you point me to it?

Thanks!

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