Type: Package
Package: mlr3mbo
Title: Flexible Bayesian Optimization
Version: 1.1.1
Authors@R: c(
    person("Marc", "Becker", , "marcbecker@posteo.de", role = c("cre", "aut"),
           comment = c(ORCID = "0000-0002-8115-0400")),
    person("Lennart", "Schneider", , "lennart.sch@web.de", role = "aut",
           comment = c(ORCID = "0000-0003-4152-5308")),
    person("Jakob", "Richter", , "jakob1richter@gmail.com", role = "aut",
           comment = c(ORCID = "0000-0003-4481-5554")),
    person("Michel", "Lang", , "michellang@gmail.com", role = "aut",
           comment = c(ORCID = "0000-0001-9754-0393")),
    person("Bernd", "Bischl", , "bernd_bischl@gmx.net", role = "aut",
           comment = c(ORCID = "0000-0001-6002-6980")),
    person("Florian", "Pfisterer", , "pfistererf@googlemail.com", role = "aut",
           comment = c(ORCID = "0000-0001-8867-762X")),
    person("Martin", "Binder", , "mlr.developer@mb706.com", role = "aut"),
    person("Sebastian", "Fischer", , "sebf.fischer@gmail.com", role = "aut",
           comment = c(ORCID = "0000-0002-9609-3197")),
    person("Michael H.", "Buselli", role = "cph"),
    person("Wessel", "Dankers", role = "cph"),
    person("Carlos", "Fonseca", role = "cph"),
    person("Manuel", "Lopez-Ibanez", role = "cph"),
    person("Luis", "Paquete", role = "cph"))
Description: A modern and flexible approach to Bayesian Optimization /
        Model Based Optimization building on the 'bbotk' package.
        'mlr3mbo' is a toolbox providing both ready-to-use optimization
        algorithms as well as their fundamental building blocks
        allowing for straightforward implementation of custom
        algorithms. Single- and multi-objective optimization is
        supported as well as mixed continuous, categorical and
        conditional search spaces. Moreover, using 'mlr3mbo' for
        hyperparameter optimization of machine learning models within
        the 'mlr3' ecosystem is straightforward via 'mlr3tuning'.
        Examples of ready-to-use optimization algorithms include
        Efficient Global Optimization by Jones et al. (1998)
        <doi:10.1023/A:1008306431147>, ParEGO by Knowles (2006)
        <doi:10.1109/TEVC.2005.851274> and SMS-EGO by Ponweiser et al.
        (2008) <doi:10.1007/978-3-540-87700-4_78>.
License: LGPL-3
URL: https://mlr3mbo.mlr-org.com, https://github.com/mlr-org/mlr3mbo
BugReports: https://github.com/mlr-org/mlr3mbo/issues
Depends: mlr3 (>= 1.2.0), mlr3tuning (>= 1.4.0), R (>= 3.1.0)
Imports: bbotk (>= 1.8.0), checkmate (>= 2.0.0), data.table, lgr (>=
        0.3.4), mlr3misc (>= 0.21.0), paradox (>= 1.0.1), spacefillr,
        R6 (>= 2.4.1)
Suggests: DiceKriging, emoa, fastGHQuad, lhs, mlr3learners (>= 0.12.0),
        mirai, mlr3pipelines (>= 0.5.2), nloptr, processx, ranger,
        rgenoud, rpart, redux, rush (>= 1.0.0), stringi, testthat (>=
        3.0.0)
ByteCompile: no
Encoding: UTF-8
Config/testthat/edition: 3
Config/testthat/parallel: false
NeedsCompilation: yes
Roxygen: list(markdown = TRUE, r6 = TRUE)
RoxygenNote: 7.3.3
Collate: 'mlr_acqfunctions.R' 'AcqFunction.R' 'AcqFunctionAEI.R'
        'AcqFunctionCB.R' 'AcqFunctionEHVI.R' 'AcqFunctionEHVIGH.R'
        'AcqFunctionEI.R' 'AcqFunctionEILog.R' 'AcqFunctionEIPS.R'
        'AcqFunctionMean.R' 'AcqFunctionMulti.R' 'AcqFunctionPI.R'
        'AcqFunctionSD.R' 'AcqFunctionSmsEgo.R'
        'AcqFunctionStochasticCB.R' 'AcqFunctionStochasticEI.R'
        'AcqOptimizer.R' 'mlr_acqoptimizers.R' 'AcqOptimizerDirect.R'
        'AcqOptimizerLbfgsb.R' 'AcqOptimizerLocalSearch.R'
        'AcqOptimzerRandomSearch.R' 'mlr_input_trafos.R' 'InputTrafo.R'
        'InputTrafoUnitcube.R' 'aaa.R' 'OptimizerADBO.R'
        'OptimizerMbo.R' 'OptimizerAsyncMbo.R' 'mlr_output_trafos.R'
        'OutputTrafo.R' 'OutputTrafoLog.R' 'OutputTrafoStandardize.R'
        'mlr_result_assigners.R' 'ResultAssigner.R'
        'ResultAssignerArchive.R' 'ResultAssignerSurrogate.R'
        'Surrogate.R' 'SurrogateLearner.R'
        'SurrogateLearnerCollection.R' 'TunerADBO.R' 'TunerAsyncMbo.R'
        'TunerMbo.R' 'mlr_loop_functions.R' 'bayesopt_ego.R'
        'bayesopt_emo.R' 'bayesopt_mpcl.R' 'bayesopt_parego.R'
        'bayesopt_smsego.R' 'bibentries.R' 'conditions.R' 'helper.R'
        'loop_function.R' 'mbo_defaults.R' 'sugar.R' 'zzz.R'
Config/pak/sysreqs: cmake make
Repository: https://mlr-org.r-universe.dev
Date/Publication: 2026-04-24 15:38:58 UTC
RemoteUrl: https://github.com/mlr-org/mlr3mbo
RemoteRef: v1.1.1
RemoteSha: 464d3ef577ead9143a1f67afc068e2d371ac0159
Packaged: 2026-06-27 13:50:54 UTC; root
Author: Marc Becker [cre, aut] (ORCID: <https://orcid.org/0000-0002-8115-0400>),
  Lennart Schneider [aut] (ORCID:
    <https://orcid.org/0000-0003-4152-5308>),
  Jakob Richter [aut] (ORCID: <https://orcid.org/0000-0003-4481-5554>),
  Michel Lang [aut] (ORCID: <https://orcid.org/0000-0001-9754-0393>),
  Bernd Bischl [aut] (ORCID: <https://orcid.org/0000-0001-6002-6980>),
  Florian Pfisterer [aut] (ORCID:
    <https://orcid.org/0000-0001-8867-762X>),
  Martin Binder [aut],
  Sebastian Fischer [aut] (ORCID:
    <https://orcid.org/0000-0002-9609-3197>),
  Michael H. Buselli [cph],
  Wessel Dankers [cph],
  Carlos Fonseca [cph],
  Manuel Lopez-Ibanez [cph],
  Luis Paquete [cph]
Maintainer: Marc Becker <marcbecker@posteo.de>