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+## LEAF-GP Benchmarks
+
+## Installation - Linux
+
+### Creating a virtual environment
+
+We use `virtualenv` to setup a virtual environment.
+You can install this package by running:
+```
+python3 -m pip install virtualenv
+```
+To set up a new virtual environment called 'env' with Python 3.7 for which this code was tested, run the command:
+```
+python3 -m virtualenv env --python=python3.7
+```
+in the folder where you want to store the virtual environment.
+Afterwards, activate the environment using
+```
+source env/bin/activate
+```
+It is recommended that you update the pip installation in the virtual environment:
+```
+pip install --upgrade pip
+```
+Install all required packages by running the command:
+```
+pip install -r requirements.txt
+```
+
+### Installlation of Gurobi 9
+Please visit the Gurobi [website](https://www.gurobi.com/downloads/end-user-license-agreement-academic/) to 
+receive an academic license and download the solver.
+To install the optimization modelling environment run:
+```
+python -m pip install -i https://pypi.gurobi.com gurobipy
+```
+
+## Run black-box function benchmarks
+As stated in the paper we evaluate black-box functions: `hartmann6d`, `rastrigin`, `styblinski_tang`, `schwefel`, 
+`g1`, `g3`, `g4`, `g6`, `g7`, `g10`, `alkylation`, `pressure_vessel` and `vae_nas`.
+To test `LEAF-GP` with the `hartmann6d` benchmark function run:
+```
+python run_study.py -bb-func hartmann6d
+```
+You can also modify the call by using optional arguments:
+- `-num-init`: number of initial data points
+- `-num-itr`: number of optimization iterations
+- `-rnd-seed`: random seed to evaluate
+- `-solver-type`: pick either `global` or `sampling`, referring to `LEAF-GP` and `LEAF-GP-RND`, respectively
+- `-has-larger-model`: picking this one uses a larger tree ensemble model for `LEAF-GP` 
+  used for the `vae_nas` benchmark