A declarative programming language built in Python, designed for the synthesis of behavioral experiments. It allows researchers to specify experiments once and seamlessly compile them into a jsPsych experiment for conducting studies with human participants or text-based simulations with synthetic participants using large-language models.
- Declarative language: Specify experiments once and compile them into a jsPsych experiment for conducting studies with human participants or text-based simulations with synthetic participants using large-language models.
- Python-based: SweetBean is built in Python, making it accessible and easy to use for researchers and educators.
This package seamlessly integrates with other packages aimed at running online behavioral experiments:
- AutoRA: For closed loop research, automatic experiment deployment, participant recruitment, and data collection.
- SweetPea: For experimental design.
But it can also be used as a standalone product.
The package is available on PyPI and can be installed via pip:
pip install sweetbeanYou can find examples and documentation here: https://autoresearch.github.io/sweetbean/
Please report any issues with this software or its documentation here.
We are open to contributions to SweetBean. More information can be found here.
We are always interested in collaborating! If you like our work but need some tailoring for your specific use case, please contact [email protected].
This project is in active development by the Autonomous Empirical Research Group, Lead Designer Younes Strittmatter, led by Sebastian Musslick.
This research program was supported by Schmidt Science Fellows, in partnership with the Rhodes Trust, as well as the Carney BRAINSTORM program at Brown University.