# **OneDTransitionRewardModel w/ SACAgent** Agent playing **mbrl-continuous-cartpole**
This is a trained model of a **OneDTransitionRewardModel w/ SACAgent** agent
playing **mbrl-continuous-cartpole**
using [MBRL-Lib](https://github.com/facebookresearch/mbrl-lib).

## Usage (with MBRL-Lib)
TODO: Add your code
```python
from mbrl import ...
...
```

{"library_name": "mbrl-lib", "tags": ["mbrl-continuous-cartpole", "deep-reinforcement-learning", "reinforcement-learning", "mbrl-lib"]}
mbrl-lib mbrl-continuous-cartpole deep-reinforcement-learning reinforcement-learning region:us
TAGS
#mbrl-lib #mbrl-continuous-cartpole #deep-reinforcement-learning #reinforcement-learning #region-us 

# OneDTransitionRewardModel w/ SACAgent Agent playing mbrl-continuous-cartpole
This is a trained model of a OneDTransitionRewardModel w/ SACAgent agent
playing mbrl-continuous-cartpole
using MBRL-Lib.

## Usage (with MBRL-Lib)
TODO: Add your code


# OneDTransitionRewardModel w/ SACAgent Agent playing mbrl-continuous-cartpole
This is a trained model of a OneDTransitionRewardModel w/ SACAgent agent
playing mbrl-continuous-cartpole
using MBRL-Lib. ## Usage (with MBRL-Lib)
TODO: Add your code
TAGS
#mbrl-lib #mbrl-continuous-cartpole #deep-reinforcement-learning #reinforcement-learning #region-us 
 # OneDTransitionRewardModel w/ SACAgent Agent playing mbrl-continuous-cartpole
This is a trained model of a OneDTransitionRewardModel w/ SACAgent agent
playing mbrl-continuous-cartpole
using MBRL-Lib. ## Usage (with MBRL-Lib)
TODO: Add your code
TAGS
#mbrl-lib #mbrl-continuous-cartpole #deep-reinforcement-learning #reinforcement-learning #region-us 
# OneDTransitionRewardModel w/ SACAgent Agent playing mbrl-continuous-cartpole
This is a trained model of a OneDTransitionRewardModel w/ SACAgent agent
playing mbrl-continuous-cartpole
using MBRL-Lib.## Usage (with MBRL-Lib)
TODO: Add your code