updated readme (again)

README.md

@@ -6,7 +6,7 @@ Multi-agent interaction planning code for RA-L submission ID: **tbd**
 
 ## Description
 
-Contains two implemented algorithms to achieve multi-agent intermittent interaction planning. In the [IIP](./IIP) directory is the novel algorithm proposed in a recent RA-L submission (submission ID: 'tbd'). While in the [HS](./HS) directory is a method from [a related work][hollinger2010] ([later extended][hollinger2012]).
+Contains two implemented algorithms to achieve multi-agent intermittent interaction planning. In the [IIP](./IIP) directory is the novel algorithm proposed in a recent RA-L submission (submission ID: `tbd`). While in the [HS](./HS) directory is a method from [a related work][hollinger2010] ([later extended][hollinger2012]).
 
 ## Table of Contents
 
@@ -19,11 +19,11 @@ Contains two implemented algorithms to achieve multi-agent intermittent interact
 
 ### Basic Usage
 
-To run IIP with randomized initial conditions, run [multi_agent_path_planning.m](./IIP/multi_agent_path_planning.m) in MATLAB. Similarly for HS, run [main.m](.HS/main.m) in MATLAB. Depending on your directory structures you may need to edit 'main.m' to change the path. Also either method may return '-1' for all outputs if there is no feasible path for all agents, which can happen when obstacles are being randomly generated as in this case.
+To run IIP with randomized initial conditions, run [multi_agent_path_planning.m](./IIP/multi_agent_path_planning.m) in MATLAB. Similarly for HS, run [main.m](.HS/main.m) in MATLAB. Depending on your directory structures you may need to edit `main.m` to change the path. Also either method may return `-1` for all outputs if there is no feasible path for all agents, which can happen when obstacles are being randomly generated as in this case.
 
 ### Monte Carlo Collection/Running
 
-To run a monte carlo simulation comparing IIP with HS on the same set of scenarios, using all available cores in the processor, run [monteCarloParallel.m](./IIP/monteCarloParallel.m). If parallel execution is not required, [monteCarloRunner.m](./IIP/monteCarloRunner.m) can be run instead. To visualize the collected data, run [monteCarloPlotter.m](./IIP/monteCarloPlotter.m). You will have to update the 'filenames' list to include the newly collected data, which is automatically generated with a time stamped file name.
+To run a monte carlo simulation comparing IIP with HS on the same set of scenarios, using all available cores in the processor, run [monteCarloParallel.m](./IIP/monteCarloParallel.m). If parallel execution is not required, [monteCarloRunner.m](./IIP/monteCarloRunner.m) can be run instead. To visualize the collected data, run [monteCarloPlotter.m](./IIP/monteCarloPlotter.m). You will have to update the `filenames` list to include the newly collected data, which is automatically generated with a time stamped file name.
 
 ## Contributing