update README

README.md

@@ -6,12 +6,13 @@ The experimental results were obtained on [Magi
 cluster](http://magi.univ-paris13.fr/wiki/) of [University Sorbonne Paris
 Nord](https://univ-paris13.fr/). We used the partition `COMPUTE` which has 40
 processors (two Intel Xeon E5-2650 v3 at 2.30GHz) connected by an InfiniBand
-network, and 64GB of RAM. A total of 4 models from the [Model Checking
+network, and 64GB of RAM. A total of 5 models from the [Model Checking
 Contest](https://mcc.lip6.fr/models.php) were used in our experiments:
 *[Philosophers](models/philo/description.pdf)* (`philo`),
 *[RobotManipulation](models/robot/description.pdf)* (`robot`),
 *[SwimmingPool](models/spool/description.pdf)*
-(`spool`), and *[CircularTrains]((models/train/description.pdf))* (`train`).
+(`spool`), *[CircularTrains]((models/train/description.pdf))* (`train`), and
+*[TokenRing](models/tring/description.pdf)* (`tring`).
 
 
 ## Clone this repository:
@@ -37,6 +38,7 @@ git clone https://depot.lipn.univ-paris13.fr/PMC-SOG/experiments/hybrid.git && c
 ├── scripts
 │   ├── csv_generator.py            # script that generates a csv file with the results from the logs
 │   ├── formula_generator.py        # script that generates N random LTL\X formulas
+│   ├── oar_formula_generator.py    # script that generates the files to run the experiments on the GRID5000 cluster
 │   └── plot-results.ipynb          # Python notebook that allows to generate the figures and interact with the results
 │   └── plot-results.py             # script that generates the figures (if you do not want to open the notebook)
 │   └── sbatch_formula_generator.py # script that generates the sbatch files to generate formulas on Magi cluster