Changes in version 1.1.1 (2026-04-24) - fix: acqo() now correctly returns the mlr_acqoptimizers dictionary when called with no arguments (#211). - fix: AcqFunctionEILog now provides a more informative error message when the surrogate is not configured with the correct output transformation. - fix: AcqOptimizerDirect and AcqOptimizerLbfgsb now correctly enforce the max_restarts limit in all cases. - fix: SurrogateLearner and SurrogateLearnerCollection now correctly apply their output transformation after imputing running evaluations. Changes in version 1.1.0 (2026-03-18) - compatibility: rush 1.0.0 (#202). - feat: Surrogate gained a $check() method (#200). Changes in version 1.0.0 (2026-02-27) - feat: Added mlr_acqoptimizers dictionary with pre-defined acquisition function optimizers (AcqOptimizerDirect, AcqOptimizerLbfgsb, AcqOptimizerLocalSearch, AcqOptimizerRandomSearch). - perf: Default surrogate model, acquisition function, optimizer, and further settings of OptimizerMbo are now empirically derived from a large-scale benchmark study, significantly improving out-of-the-box optimization performance. - feat: Added Mlr3ErrorMbo* condition classes. Changes in version 0.3.3 (2025-10-10) - compatibility: bbotk 1.7.0 Changes in version 0.3.2 (2025-10-02) - compatibility: mlr3learners 0.13.0 Changes in version 0.3.1 (2025-08-19) - chore: maintainer change. - chore: work with new mlr3pipelines version 0.9.0 (fix for tests only). - test: expect_rush_reset changes related to rush developments. - fix: allow InputTrafoUnitcube to work in mixed spaces. Changes in version 0.3.0 (2025-06-03) - fix: logger changes related to bbotk. - fix: assure that candidates after acquisition function optimization are always within bounds. - perf: minor changes to speed up predictions with SurrogateLearner and SurrogateLearnerCollection. - feat: added supported for input and output transformations (see InputTrafo, OutputTrafo and the related classes). - refactor: dropped functionality to assert insample performance of the surrogate model completely. Changes in version 0.2.9 (2025-03-04) - chore: silence rush logger and fixed some partial matches, depend on mlr3 >= 0.22.1. - test: fix test_AcqFunctionMulti, robustify helper and loading. - test: fix test_ResultAssignerArchive and test_ResultAssignerSurrogate due to upcoming changes of internal tuned values in mlr3tuning 1.3.1. Changes in version 0.2.8 (2024-11-21) - docs: gracefully exit examples of OptimizerAsyncMbo, OptimizerADBO, TunerAsyncMbo, and TunerADBO if Redis is not available. - test: skip tests involving asynchronous logic if Redis is not available. Changes in version 0.2.7 (2024-11-15) - refactor: refactored SurrogateLearner and SurrogateLearnerCollection to allow updating on an asynchronous Archive. - feat: added experimental OptimizerAsyncMbo, OptimizerADBO, TunerAsyncMbo, and TunerADBO that allow for asynchronous optimization. - feat: added AcqFunctionStochasticCB and AcqFunctionStochasticEI that are useful for asynchronous optimization. - docs: minor changes to highlight differences between batch and asynchronous objects related to asynchronous support. - refactor: AcqFunctions and AcqOptimizer gained a reset() method. Changes in version 0.2.6 (2024-10-16) - refactor: extract internal tuned values in instance. Changes in version 0.2.5 (2024-09-24) - docs: move vignette to mlr3book. - feat: add AcqFunctionMulti that can wrap multiple acquisition functions resulting in a multi-objective acquisition function problem. - feat: support callbacks in AcqOptimizer. - feat: allow AcqFunctionEI to be adjusted by epsilon to strengthen exploration. Changes in version 0.2.4 (2024-07-06) - fix: improve runtime of AcqOptimizer by setting check_values = FALSE. Changes in version 0.2.3 (2024-07-01) - compatibility: work with new bbotk and mlr3tuning version 1.0.0. Changes in version 0.2.2 (2024-03-01) - refactor: compatibility with upcoming paradox upgrade. - feat: OptimizerMbo and TunerMbo now update the Surrogate a final time after the optimization process finished to ensure that the Surrogate correctly reflects the state of being trained on all data seen during optimization. - fix: AcqFunction domain construction now respects Surrogate cols_x field. - feat: support more than one candidate point as a result of acquisition function optimization even for non-batch acquisition functions. - feat: added default_gp and default_rf helpers that allow for construction of a default Gaussian Process and random forest as for example used within default_surrogate. - refactor: changed Gaussian Process and random forest defaults (in default_gp and default_rf and therefore also in default_surrogate). Gaussian Process now uses a "matern5_2" kernel. Random forest now uses 100 trees. The number of trees used in the fallback random forest was reduced to 10. Changes in version 0.2.1 (2023-06-05) - docs: updated some references in vignette. - refactor: minor clean up of the internal structure of all loop functions. - perf: default initial design constructed based on a Sobol sequence in all loop functions. - refactor: no longer depend on mlr3tuning but import instead. - refactor: srlrn sugar function now can construct both a SurrogateLearner and SurrogateLearnerCollection; dropped srlrnc. - feat: added AcqFunctionSD, AcqFunctionEHVI and AcqFunctionEHVIGH, introduced bayesopt_emo loop function. - feat: AcqFunctions now include a $packages field stating required packages which are checked for whether their namespace can be loaded prior to optimization. - fix: fixed bug in fix_xdt_missing() helper function. - BREAKING CHANGE: renaming default_loopfun -> default_loop_function, default_acqfun -> default_acqfunction, default_acqopt -> default_acqoptimizer. - BREAKING CHANGE: result_functions now replaced by ResultAssigners. - BREAKING CHANGE: renamed $model field of all Surrogate classes to $learner. - BREAKING CHANGE: For all Surrogate and AcquisitionFunction classes fields *_cols renamed to cols_* (e.g., x_cols to cols_x). Changes in version 0.1.2 (2023-03-02) - refactor: adapt to mlr3tuning 0.18.0. - feat: acquisition functions now assert whether surrogates match their required predict type. - fix: unloading mlr3mbo removes optimizers and tuners from the dictionaries. - docs: faster examples. - feat: characters in surrogate regression tasks are no longer automatically converted to factors. default_surrogate now respects this and gained an appropriate pipeline step. - feat: AcqFunctionAEI added. - docs: fix of docs, README and bibentries. Changes in version 0.1.1 (2022-11-18) - Initial upload to CRAN.