OptimizerCmaes class that implements CMA-ES. Calls adagio::pureCMAES() from package adagio.

Dictionary

This Optimizer can be instantiated via the dictionary mlr_optimizers or with the associated sugar function opt():

mlr_optimizers$get("cmaes")
opt("cmaes")

Parameters

sigma

numeric(1)

start_values

character(1)
Create random start values or based on center of search space? In the latter case, it is the center of the parameters before a trafo is applied.

For the meaning of the control parameters, see adagio::pureCMAES(). Note that we have removed all control parameters which refer to the termination of the algorithm and where our terminators allow to obtain the same behavior.

Progress Bars

$optimize() supports progress bars via the package progressr combined with a Terminator. Simply wrap the function in progressr::with_progress() to enable them. We recommend to use package progress as backend; enable with progressr::handlers("progress").

Super class

bbotk::Optimizer -> OptimizerCmaes

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage

OptimizerCmaes$new()


Method clone()

The objects of this class are cloneable with this method.

Usage

OptimizerCmaes$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

if(requireNamespace("adagio")) { library(paradox) domain = ParamSet$new(list(ParamDbl$new("x", lower = -1, upper = 1))) search_space = ParamSet$new(list(ParamDbl$new("x", lower = -1, upper = 1))) codomain = ParamSet$new(list(ParamDbl$new("y", tags = "minimize"))) objective_function = function(xs) { list(y = as.numeric(xs)^2) } objective = ObjectiveRFun$new(fun = objective_function, domain = domain, codomain = codomain) terminator = trm("evals", n_evals = 10) instance = OptimInstanceSingleCrit$new( objective = objective, search_space = search_space, terminator = terminator) optimizer = opt("cmaes") # Modifies the instance by reference optimizer$optimize(instance) # Returns best scoring evaluation instance$result # Allows access of data.table of full path of all evaluations as.data.table(instance$archive$data) }
#> Loading required namespace: adagio
#> x y x_domain timestamp batch_nr #> 1: 0.1329308 0.0176706 <list[1]> 2021-01-24 15:47:15 1 #> 2: -1.0000000 1.0000000 <list[1]> 2021-01-24 15:47:15 2 #> 3: -0.9228386 0.8516311 <list[1]> 2021-01-24 15:47:15 3 #> 4: -1.0000000 1.0000000 <list[1]> 2021-01-24 15:47:15 4 #> 5: 0.6399486 0.4095342 <list[1]> 2021-01-24 15:47:15 5 #> 6: -0.9668598 0.9348178 <list[1]> 2021-01-24 15:47:15 6 #> 7: -0.5195898 0.2699736 <list[1]> 2021-01-24 15:47:15 7 #> 8: -0.8927007 0.7969145 <list[1]> 2021-01-24 15:47:15 8 #> 9: -1.0000000 1.0000000 <list[1]> 2021-01-24 15:47:15 9 #> 10: 0.9315356 0.8677585 <list[1]> 2021-01-24 15:47:15 10