39 lines
1 KiB
Markdown
39 lines
1 KiB
Markdown
# Brittle Star
|
|
|
|
> What is the impact of different levels of controller-modularity on the learning-speed, coordination and tolerance for
|
|
defects (e.g. amputations) in brittle-star-like robots trained with Reinforcement Learning?
|
|
|
|
## Quick start
|
|
|
|
### Local setup
|
|
|
|
To set up the UV module, you can run the following command:
|
|
|
|
```bash
|
|
uv sync --frozen
|
|
```
|
|
|
|
## Usage
|
|
|
|
For detailed instructions on how to use the project, please refer to the **[API Documentation](docs/README.md)**.
|
|
|
|
### Quick Start
|
|
|
|
1. **Train a model:**
|
|
```bash
|
|
uv run python scripts/train.py ppo.learning_rate=0.001 logging.track=true
|
|
```
|
|
|
|
2. **Monitor progress:**
|
|
See [Tracking & Monitoring](docs/api/tracking.md).
|
|
|
|
3. **Simulate a trained model:**
|
|
See [Simulation & Evaluation](docs/api/simulation.md).
|
|
|
|
## HPC
|
|
|
|
See **[docs/HPC.md](docs/HPC.md)** for the full guide, including environment setup, cluster selection, interactive debugging, and job submission.
|
|
|
|
## Documentation
|
|
|
|
Please find all documentation and a starting point for more information in [corresponding README](./docs/README.md).
|