Added off-the-shelf optimisation and updated documentation

Author: mikediessner

README.md

@@ -12,14 +12,14 @@ clean and comprehensible code, precise references, and thorough documentation.
 User experience is ensured by a modular and flexible design, easy-to-write
 syntax, and careful selection of Bayesian optimisation algorithms. NUBO allows
 you to tailor Bayesian optimisation to your specific problem by writing the
-optimisation loop yourself using the provided building blocks. Only algorithms
-and methods that are sufficiently tested and validated to perform well are
-included in NUBO. This ensures that the package remains compact and does not
-overwhelm the user with an unnecessary large number of options. The package is
-written in [Python](https://www.python.org) but does not require expert
-knowledge of Python to optimise your simulations and experiments. NUBO is
-distributed as an open-source software under the
-[BSD 3-Clause licence](https://joinup.ec.europa.eu/licence/bsd-3-clause-new-or-revised-license).
+optimisation loop yourself using the provided building blocks or using an
+off-the-shelf algorithm for common problems. Only algorithms and methods that
+are sufficiently tested and validated to perform well are included in NUBO. This
+ensures that the package remains compact and does not overwhelm the user with an
+unnecessary large number of options. The package is written in
+[Python](https://www.python.org) but does not require expert knowledge of Python
+to optimise your simulations and experiments. NUBO is distributed as an
+open-source software under the [BSD 3-Clause licence](https://joinup.ec.europa.eu/licence/bsd-3-clause-new-or-revised-license).
 
  > Thanks for considering NUBO. If you have any questions, comments, or issues
  > feel free to email us at [email protected]. Any feedback is highly
@@ -38,14 +38,14 @@ following code. We recommend the use of a virtual environment.S
 
 If you are using NUBO for your research, please cite as:
 
-    Mike Diessner, Kevin Wilson, and Richard D. Whalley. "NUBO: A Transparent Python Package for Bayesian Optimisation," arXiv preprint arXiv:2305.06709, 2023.
+    Mike Diessner, Kevin J. Wilson, and Richard D. Whalley. "NUBO: A Transparent Python Package for Bayesian Optimisation," arXiv preprint arXiv:2305.06709, 2023.
 
 If you are using Bibtex, please cite as:
 
 ```
 @article{diessner2023nubo,
          title={NUBO: A Transparent Python Package for Bayesian Optimisation},
-         author={Diessner, Mike and Wilson, Kevin and Whalley, Richard D},
+         author={Diessner, Mike and Wilson, Kevin J and Whalley, Richard D},
          journal={arXiv preprint arXiv:2305.06709},
          year={2023}
 }