Section: New Software and Platforms

Limbo

LIbrary for Model-based Bayesian Optimization

Keywords: Black-box optimization - C++ - Global optimization - Machine learning - Policy Learning - Bayesian optimization - Gaussian processes

Functional Description: Limbo is an open-source C++11 library for Gaussian processes and Bayesian Optimization which is designed to be both highly flexible and very fast. It can be used to optimize functions for which the gradient is unknown, evaluations are expensive, and where runtime cost matters (e.g., on embedded systems or robots). Benchmarks on standard functions show that Limbo is about 2 times faster than BayesOpt (another C++ library) for a similar accuracy.

News Of The Year: - publication of a paper in the Journal of Open Source Software - several bug fixes and performance improvement

• Partners: UPMC - Imperial College London

• Contact: Jean-Baptiste Mouret

• Publication: Limbo: A Flexible High-performance Library for Gaussian Processes modeling and Data-Efficient Optimization

• URL: http://www.resibots.eu/limbo