pySOT is a collection of synchronous and asynchronous surrogate optimization strategies, implemented in the POAP framework ( We support the stochastic RBF method by Regis and Shoemaker along with various extensions of this method and a general surrogate optimization strategy which covers most Bayesian optimization methods. We have implemented many different surrogate models, experimental designs, auxiliary problems (also known as acquisition functions), and a large set of test problems. The object-oriented design makes it easy to add new surrogate models, experimental designs, and auxiliary problems and use them within the framework.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 1 article )

Showing result 1 of 1.
Sorted by year (citations)

  1. Costa, Alberto; Nannicini, Giacomo: RBFOpt: an open-source library for black-box optimization with costly function evaluations (2018)