Skip to content

TUHH-ICS/2025-code-An-Analysis-of-Safety-Guarantees-in-Multi-Task-Bayesian-Optimization

Folders and files

NameName
Last commit message
Last commit date

Latest commit

04afc28 · Mar 17, 2025

History

7 Commits
Mar 10, 2025
Mar 10, 2025
Mar 11, 2025
Mar 10, 2025
Mar 10, 2025
Mar 10, 2025
Mar 17, 2025
Mar 10, 2025
Mar 10, 2025
Mar 10, 2025
Mar 10, 2025
Mar 17, 2025
Mar 11, 2025
Mar 10, 2025

Repository files navigation

An Analysis of Safety Guarantees in Multi-Task Bayesian Optimization

General

This repository contains supplementary material and the code to reproduce the tables and figures presented in

J. O. Lübsen, A. Eichler, "An Anlysis of Safety Guarantees in Multi-Task Bayesian Optimization"

To run the proposed SaMSBO algorithm, the user can use the 'run_SaMSBO.py' file. To run the safe UCB algorithm for comparison, the user can use the 'run_SafeUCB.py' file. Additionally, there is a Jupyter notebook 'visualized_example.ipynb' which shows the optimization of a one-dimensional example. This can be run to visually follow the optimization procedure.

The data used for plots to generate the figures in the manuscript are in the data folder. The user can use the 'generate_plots.ipynb' notebook to recreate the figures in the 'plot_scripts' folder.

Prerequisites

To run the code install python3.12.8 and the dependencies specified in requirements.txt.

pip install -r requirements.txt

The code in this repository was tested in the following environment:

  • *Ubuntu 24.04.2 LTS
  • *Python 3.12.8

About

No description, website, or topics provided.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published