Limbo’s documentation

Limbo is a lightweight framework for Bayesian Optimization, a powerful approach for global optimization of expensive, non-convex functions. Github page (to report issues and/or help us to improve the library): [Github repository]

The development of Limbo is funded by the ERC project ResiBots.

Limbo shares many ideas with Sferes2, a similar framework for evolutionary computation.

Main features

  • Implementation of the classic algorithms (Bayesian optimization, many kernels, likelihood maximization, etc.)
  • Modern C++-11
  • Generic framework (template-based / policy-based design), which allows for easy customization, to test novel ideas
  • Experimental framework that allows user to easily test variants of experiments, compare treatments, submit jobs to clusters (OAR scheduler), etc.
  • High performance (in particular, Limbo can exploit multicore computers via Intel TBB and vectorize some operations via Eigen3)
  • Purposely small to be easily maintained and quickly understood