ROBOT tutorial notebook (#2883)

Summary:
<!--
Thank you for sending the PR! We appreciate you spending the time to make BoTorch better.

Help us understand your motivation by explaining why you decided to make this change.

You can learn more about contributing to BoTorch here: https://github.com/pytorch/botorch/blob/main/CONTRIBUTING.md
-->

## Motivation

This PR adds a tutorial notebook for the Rank Ordered Bayesian Optimization with Trust Regions (ROBOT) method proposed by the AISTATS 2023 paper titled Discovering Many Diverse Solutions with Bayesian Optimization. The motivation for the notebook is to provide a simple clean example of how the ROBOT method can be applied in practice to optimize a set of diverse solutions to a black-box objective function.

### Have you read the [Contributing Guidelines on pull requests](https://github.com/pytorch/botorch/blob/main/CONTRIBUTING.md#pull-requests)?

Yes.

Pull Request resolved: #2883

Test Plan:
The only change made is to add an isolated Jupyter notebook (robot.ipynb) to the tutorials folder. I checked that the notebook runs as it should and produces desired outputs. Since none of the BoTorch code was actually changed at all (all I did was add this notebook), no other tests are required as far as I am aware.

## Related PRs

(If this PR adds or changes functionality, please take some time to update the docs at https://github.com/pytorch/botorch, and link to your PR here.)

Reviewed By: Balandat

Differential Revision: D76821185

Pulled By: esantorella

fbshipit-source-id: 5d1d3228cd4bb0c5e620d088fd67b222131153ef

Author: nataliemaus