| .. _rl-frameworks: |
| |
| Reinforcement Learning Library Comparison |
| ========================================= |
| |
| In this section, we provide an overview of the supported reinforcement learning libraries in Isaac Lab, |
| along with performance benchmarks across the libraries. |
| |
| The supported libraries are: |
| |
| - `SKRL <https://skrl.readthedocs.io>`__ |
| - `RSL-RL <https://github.com/leggedrobotics/rsl_rl>`__ |
| - `RL-Games <https://github.com/Denys88/rl_games>`__ |
| - `Stable-Baselines3 <https://stable-baselines3.readthedocs.io/en/master/index.html>`__ |
|
|
| Feature Comparison |
| ------------------ |
|
|
| .. list-table:: |
| :widths: 20 20 20 20 20 |
| :header-rows: 1 |
|
|
| * - Feature |
| - RL-Games |
| - RSL RL |
| - SKRL |
| - Stable Baselines3 |
| * - Algorithms Included |
| - PPO, SAC, A2C |
| - PPO, Distillation |
| - `Extensive List <https://skrl.readthedocs.io/en/latest/#agents>`__ |
| - `Extensive List <https://github.com/DLR-RM/stable-baselines3?tab=readme-ov-file#implemented-algorithms>`__ |
| * - Vectorized Training |
| - Yes |
| - Yes |
| - Yes |
| - No |
| * - Distributed Training |
| - Yes |
| - Yes |
| - Yes |
| - No |
| * - ML Frameworks Supported |
| - PyTorch |
| - PyTorch |
| - PyTorch, JAX |
| - PyTorch |
| * - Multi-Agent Support |
| - PPO |
| - PPO |
| - PPO + Multi-Agent algorithms |
| - External projects support |
| * - Documentation |
| - Low |
| - Low |
| - Comprehensive |
| - Extensive |
| * - Community Support |
| - Small Community |
| - Small Community |
| - Small Community |
| - Large Community |
| * - Available Examples in Isaac Lab |
| - Large |
| - Large |
| - Large |
| - Small |
|
|
|
|
| Training Performance |
| -------------------- |
|
|
| We performed training with each RL library on the same ``Isaac-Humanoid-v0`` environment |
| with ``--headless`` on a single NVIDIA GeForce RTX 4090 and logged the total training time |
| for 65.5M steps (4096 environments x 32 rollout steps x 500 iterations). |
|
|
| +--------------------+-----------------+ |
| | RL Library | Time in seconds | |
| +====================+=================+ |
| | RL-Games | 201 | |
| +--------------------+-----------------+ |
| | SKRL | 201 | |
| +--------------------+-----------------+ |
| | RSL RL | 198 | |
| +--------------------+-----------------+ |
| | Stable-Baselines3 | 287 | |
| +--------------------+-----------------+ |
|
|
| Training commands (check for the *'Training time: XXX seconds'* line in the terminal output): |
|
|
| .. code:: bash |
|
|
| python scripts/reinforcement_learning/rl_games/train.py --task Isaac-Humanoid-v0 --max_iterations 500 --headless |
| python scripts/reinforcement_learning/skrl/train.py --task Isaac-Humanoid-v0 --max_iterations 500 --headless |
| python scripts/reinforcement_learning/rsl_rl/train.py --task Isaac-Humanoid-v0 --max_iterations 500 --headless |
| python scripts/reinforcement_learning/sb3/train.py --task Isaac-Humanoid-v0 --max_iterations 500 --headless |
| |
