metadata
library_name: stable-baselines3
tags:
- PandaReachDense-v3
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaReachDense-v3
type: PandaReachDense-v3
metrics:
- type: mean_reward
value: '-0.56 +/- 1.08'
name: mean_reward
verified: false
A2C Agent playing PandaReachDense-v3
This is a trained model of a A2C agent playing PandaReachDense-v3 using the stable-baselines3 library.
Usage (with Stable-baselines3)
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...
Please check article for further description: https://medium.com/@andysingal/deep-q-learning-to-actor-critic-using-robotics-simulations-with-panda-gym-ff220f980366?sk=065b306d15fea64e667c6dc5d0a4411f