Exploration objective

The objective is to learn the global behaviour of a target variable by exploring regions with large information gain. New samples are selected where the model’s prediction uncertainty is large. Evaluations that are already running are taken into account when estimating how much uncertainty a new sample can reduce. This helps distribute parallel evaluations across informative regions.

name (str)

The name of the objective.

Default: "objective"

variable (str)

The name of a single-output variable that specifies the objective value.

Default: The first variable in the list of all variables.

penalize_boundaries (bool)

If true, the uncertainty is penalized by a small distance to the domain boundary.

Default: false

min_uncertainty (float)

The study is stopped if the uncertainty (square root of variance) of the objective at the last 5 sampling points was below min_uncertainty.

Default: 0.0

strategy (str)

Exploration strategy.

Default: "uncertainty" Choices: "uncertainty".