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a2c-PandaReachDense-v2
Felix555/a2c-PandaReachDense-v2
a2c-PandaReachDense-v2 is a reinforcement learning model from Felix555. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for stable-baselines3.
This is a trained model of a A2C agent playing PandaReachDense-v2 using the stable-baselines3 library. This paper presents panda-gym, a set of Reinforcement Learning (RL) environments for the Franka Emika Panda robot…
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At a glance
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Access
- Public
- Created
- May 11, 2023
- Updated
- Aug 21, 2023
- SHA
- 96692cec
Model card
From the Hugging Face model README
A2C Agent playing PandaReachDense-v2
This is a trained model of a A2C agent playing PandaReachDense-v2 using the stable-baselines3 library. This paper presents panda-gym, a set of Reinforcement Learning (RL) environments for the Franka Emika Panda robot integrated with OpenAI Gym. Five tasks are included: reach, push, slide, pick & place and stack. They all follow a Multi-Goal RL framework, allowing to use goal-oriented RL algorithms. To foster open-research, we chose to use the open-source physics engine PyBullet. The implementation chosen for this package allows to define very easily new tasks or new robots. This paper also presents a baseline of results obtained with state-of-the-art model-free off-policy algorithms. panda-gym is open-source and freely available at https://github.com/qgallouedec/panda-gym.
Usage (with Stable-baselines3)
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Created
- May 11, 2023
- Updated
- Aug 21, 2023