cleanup DESCRIPTION

DESCRIPTION

@@ -1,49 +1,88 @@
 Package: mlrMBO
 Title: Bayesian Optimization and Model-Based Optimization of Expensive
-        Black-Box Functions
-Version: 1.1.5.1
-Description: Flexible and comprehensive R toolbox for model-based optimization
-    ('MBO'), also known as Bayesian optimization. It implements the Efficient
-    Global Optimization Algorithm and is designed for both single- and multi-
-    objective optimization with mixed continuous, categorical and conditional
-    parameters. The machine learning toolbox 'mlr' provide dozens of regression
-    learners to model the performance of the target algorithm with respect to
-    the parameter settings. It provides many different infill criteria to guide
-    the search process. Additional features include multi-point batch proposal,
-    parallel execution as well as visualization and sophisticated logging
-    mechanisms, which is especially useful for teaching and understanding of
-    algorithm behavior. 'mlrMBO' is implemented in a modular fashion, such that
-    single components can be easily replaced or adapted by the user for specific
-    use cases.
-Authors@R: c(
-    person("Bernd", "Bischl", email = "bernd_bischl@gmx.net", role = c("aut"), comment = c(ORCID = "0000-0001-6002-6980")),
-    person("Jakob", "Richter", email = "code@jakob-r.de", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4481-5554")),
-    person("Jakob", "Bossek", email = "j.bossek@gmail.com", role = "aut", comment = c(ORCID = "0000-0002-4121-4668")),
-    person("Daniel", "Horn", email = "daniel.horn@tu-dortmund.de", role = "aut"),
-    person("Michel", "Lang", email = "michellang@gmail.com", role = "aut", comment = c(ORCID = "0000-0001-9754-0393")),
-    person("Janek", "Thomas", email = "janek.thomas@stat.uni-muenchen.de", role = "aut", comment = c(ORCID = "0000-0003-4511-6245")))
+    Black-Box Functions
+Version: 1.1.5-9000
+Authors@R: 
+    c(person(given = "Bernd",
+             family = "Bischl",
+             role = "aut",
+             email = "bernd_bischl@gmx.net",
+             comment = c(ORCID = "0000-0001-6002-6980")),
+      person(given = "Jakob",
+             family = "Richter",
+             role = c("aut", "cre"),
+             email = "code@jakob-r.de",
+             comment = c(ORCID = "0000-0003-4481-5554")),
+      person(given = "Jakob",
+             family = "Bossek",
+             role = "aut",
+             email = "j.bossek@gmail.com",
+             comment = c(ORCID = "0000-0002-4121-4668")),
+      person(given = "Daniel",
+             family = "Horn",
+             role = "aut",
+             email = "daniel.horn@tu-dortmund.de"),
+      person(given = "Michel",
+             family = "Lang",
+             role = "aut",
+             email = "michellang@gmail.com",
+             comment = c(ORCID = "0000-0001-9754-0393")),
+      person(given = "Janek",
+             family = "Thomas",
+             role = "aut",
+             email = "janek.thomas@stat.uni-muenchen.de",
+             comment = c(ORCID = "0000-0003-4511-6245")))
+Description: Flexible and comprehensive R toolbox for model-based
+    optimization ('MBO'), also known as Bayesian optimization. It
+    implements the Efficient Global Optimization Algorithm and is designed
+    for both single- and multi- objective optimization with mixed
+    continuous, categorical and conditional parameters. The machine
+    learning toolbox 'mlr' provide dozens of regression learners to model
+    the performance of the target algorithm with respect to the parameter
+    settings. It provides many different infill criteria to guide the
+    search process. Additional features include multi-point batch
+    proposal, parallel execution as well as visualization and
+    sophisticated logging mechanisms, which is especially useful for
+    teaching and understanding of algorithm behavior. 'mlrMBO' is
+    implemented in a modular fashion, such that single components can be
+    easily replaced or adapted by the user for specific use cases.
 License: BSD_2_clause + file LICENSE
 URL: https://github.com/mlr-org/mlrMBO
 BugReports: https://github.com/mlr-org/mlrMBO/issues
-Depends: mlr (>= 2.10), ParamHelpers (>= 1.10), smoof (>= 1.5.1)
-Imports: backports (>= 1.1.0), BBmisc (>= 1.11), checkmate (>= 1.8.2),
-        data.table, lhs, parallelMap (>= 1.3)
-Suggests: cmaesr (>= 1.0.3), ggplot2, DiceKriging, earth, emoa, GGally,
-        gridExtra, kernlab, kknn, knitr, mco, nnet, party,
-        randomForest, reshape2, rmarkdown, rgenoud, rpart, testthat,
-        covr
-Encoding: UTF-8
+Depends:
+    mlr (>= 2.10),
+    ParamHelpers (>= 1.10),
+    smoof (>= 1.5.1)
+Imports:
+    backports (>= 1.1.0),
+    BBmisc (>= 1.11),
+    checkmate (>= 1.8.2),
+    data.table,
+    lhs,
+    parallelMap (>= 1.3)
+Suggests:
+    cmaesr (>= 1.0.3),
+    covr,
+    DiceKriging,
+    earth,
+    emoa,
+    GGally,
+    ggplot2,
+    gridExtra,
+    kernlab,
+    kknn,
+    knitr,
+    mco,
+    nnet,
+    party,
+    randomForest,
+    reshape2,
+    rgenoud,
+    rmarkdown,
+    rpart,
+    testthat
+VignetteBuilder: 
+    knitr
 ByteCompile: yes
+Encoding: UTF-8
 RoxygenNote: 7.1.1
-VignetteBuilder: knitr
-NeedsCompilation: yes
-Packaged: 2022-07-04 07:35:16 UTC; ripley
-Author: Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>),
-  Jakob Richter [aut, cre] (<https://orcid.org/0000-0003-4481-5554>),
-  Jakob Bossek [aut] (<https://orcid.org/0000-0002-4121-4668>),
-  Daniel Horn [aut],
-  Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>),
-  Janek Thomas [aut] (<https://orcid.org/0000-0003-4511-6245>)
-Maintainer: Jakob Richter <code@jakob-r.de>
-Repository: CRAN
-Date/Publication: 2022-07-04 08:50:50 UTC