https://github.com/befelix/safeopt

Safe Bayesian Optimization
https://github.com/befelix/safeopt

gaussian-processes optimization reinforcement-learning robotics safety

Last synced: 6 days ago
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Safe Bayesian Optimization

• Host: GitHub
• URL: https://github.com/befelix/safeopt
• Owner: befelix
• License: mit
• Created: 2015-07-21T09:44:35.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2022-11-14T10:45:15.000Z (about 2 years ago)
• Last Synced: 2025-01-08T12:07:13.960Z (14 days ago)
• Topics: gaussian-processes, optimization, reinforcement-learning, robotics, safety
• Language: Python
• Homepage:
• Size: 317 KB
• Stars: 142
• Watchers: 8
• Forks: 51
• Open Issues: 2
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

Awesome Lists containing this project

README

        
====================================

SafeOpt - Safe Bayesian Optimization

====================================

.. image:: https://travis-ci.org/befelix/SafeOpt.svg?branch=master

  :target: https://travis-ci.org/befelix/SafeOpt

  :alt: Build Status

.. image:: https://readthedocs.org/projects/safeopt/badge/?version=latest

  :target: http://safeopt.readthedocs.io/en/latest/?badge=latest

  :alt: Documentation Status

This code implements an adapted version of the safe, Bayesian optimization algorithm, SafeOpt [1]_, [2]_. It also provides a more scalable implementation based on [3]_ as well as an implementation for the original algorithm in [4]_.

The code can be used to automatically optimize a performance measures subject to a safety constraint by adapting parameters.

The prefered way of citing this code is by referring to [1] or [2].

.. image:: http://img.youtube.com/vi/GiqNQdzc5TI/0.jpg

  :target: http://www.youtube.com/watch?feature=player_embedded&v=GiqNQdzc5TI

  :alt: Youtube video

.. [1] F. Berkenkamp, A. P. Schoellig, A. Krause,

  `Safe Controller Optimization for Quadrotors with Gaussian Processes `_

  in Proc. of the IEEE International Conference on Robotics and Automation (ICRA), 2016, pp. 491-496.

.. [2] F. Berkenkamp, A. Krause, A. P. Schoellig,

  `Bayesian Optimization with Safety Constraints: Safe and Automatic Parameter Tuning in Robotics  `_,

  ArXiv, 2016, arXiv:1602.04450 [cs.RO].

.. [3] Rikky R.P.R. Duivenvoorden, Felix Berkenkamp, Nicolas Carion, Andreas Krause, Angela P. Schoellig,

  `Constrained Bayesian optimization with Particle Swarms for Safe Adaptive Controller Tuning `_,

  in Proc. of the IFAC (International Federation of Automatic Control) World Congress, 2017.

.. [4] Y. Sui, A. Gotovos, J. W. Burdick, and A. Krause,

  `Safe exploration for optimization with Gaussian processes `_

  in Proc. of the International Conference on Machine Learning (ICML), 2015, pp. 997–1005.

Warning: Maintenance mode

-------------------------

This package is no longer actively maintained. That bein said, pull requests to add functionality or fix bugs are always welcome.

Installation

------------

The easiest way to install the necessary python libraries is by installing pip (e.g. ``apt-get install python-pip`` on Ubuntu) and running

``pip install safeopt``

Alternatively you can clone the repository and install it using

``python setup.py install``

Usage

-----

*The easiest way to get familiar with the library is to run the interactive example ipython notebooks!*

Make sure that the ``ipywidgets`` module is installed. All functions and classes are documented on `Read The Docs `_.

License

-------

The code is licenced under the MIT license and free to use by anyone without any restrictions.