random_search: IOHexperimenter-based wrapper

In IOHexperimenter: Benchmarking Part of the 'IOHprofiler'

Description

For easier use with the IOHexperimenter

Random walk in {0, 1}^d space; Maximization

Random walk in continuous space;

Usage

IOH_random_search(IOHproblem, budget = NULL)

random_search_PB(dim, obj_func, target_hit = function() {     FALSE },
  budget = NULL)

random_search(dim, obj_func, target_hit = function() {     FALSE },
  budget = NULL, lbound = -1, ubound = 1, maximize = T)

Arguments

IOHproblem	An IOHproblem object
budget	Integer, maximal allowable number of function evaluations
dim	Dimension of search space
obj_func	The evaluation function
target_hit	Optional, function which enables early stopping if a target value is reached
lbound	Lower bound of search space. Either single number or vector of size 'dim'
ubound	Upper bound of search space. Either single number or vector of size 'dim'
maximize	Whether to perform maximization or minimization. The function assumes minimization, achieved by inverting the obj_func when 'maximize' is FALSE

Examples

benchmark_algorithm(IOH_random_search, data.dir = NULL)

IOHexperimenter documentation built on Sept. 1, 2020, 5:08 p.m.