
# **A2C** Agent playing **PandaReachDense-v2**
This is a trained model of a **A2C** agent playing **PandaReachDense-v2**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.

## Usage (with SB3 RL Zoo)

RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
SB3: https://github.com/DLR-RM/stable-baselines3<br/>
SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib

```
# Download model and save it into the logs/ folder
python -m rl_zoo3.load_from_hub --algo tqc --env PandaReachDense-v2 -orga sb3 -f logs/
python enjoy.py --algo a2c --env PandaReachDense-v2  -f logs/
```

## Training (with the RL Zoo)
```
python train.py --algo a2c --env PandaReachDense-v2 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo a2c --env PandaReachDense-v2 -f logs/ -orga sb3
```


Panda Gym environments: [arxiv.org/abs/2106.13687](https://arxiv.org/abs/2106.13687)
{"library_name": "stable-baselines3", "tags": ["PandaReachDense-v2", "deep-reinforcement-learning", "reinforcement-learning", "stable-baselines3"], "model-index": [{"name": "A2C", "results": [{"task": {"type": "reinforcement-learning", "name": "reinforcement-learning"}, "dataset": {"name": "PandaReachDense-v2", "type": "PandaReachDense-v2"}, "metrics": [{"type": "mean_reward", "value": "-1.39 +/- 0.30", "name": "mean_reward", "verified": false}]}]}]}
stable-baselines3 PandaReachDense-v2 deep-reinforcement-learning reinforcement-learning arxiv:2106.13687 model-index region:us
TAGS
#stable-baselines3 #PandaReachDense-v2 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us 


# A2C Agent playing PandaReachDense-v2
This is a trained model of a A2C agent playing PandaReachDense-v2
using the stable-baselines3 library.

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.

## Usage (with SB3 RL Zoo)

RL Zoo: URL
SB3: URL
SB3 Contrib: URL



## Training (with the RL Zoo)



Panda Gym environments: URL
# A2C Agent playing PandaReachDense-v2
This is a trained model of a A2C agent playing PandaReachDense-v2
using the stable-baselines3 library.

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo)

RL Zoo: URL
SB3: URL
SB3 Contrib: URL ## Training (with the RL Zoo)



Panda Gym environments: URL
TAGS
#stable-baselines3 #PandaReachDense-v2 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us 
 # A2C Agent playing PandaReachDense-v2
This is a trained model of a A2C agent playing PandaReachDense-v2
using the stable-baselines3 library.

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo)

RL Zoo: URL
SB3: URL
SB3 Contrib: URL ## Training (with the RL Zoo)



Panda Gym environments: URL
TAGS
#stable-baselines3 #PandaReachDense-v2 #deep-reinforcement-learning #reinforcement-learning #arxiv-2106.13687 #model-index #region-us 
# A2C Agent playing PandaReachDense-v2
This is a trained model of a A2C agent playing PandaReachDense-v2
using the stable-baselines3 library.

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.## Usage (with SB3 RL Zoo)

RL Zoo: URL
SB3: URL
SB3 Contrib: URL## Training (with the RL Zoo)



Panda Gym environments: URL