Experiments for "It's Time to Play Safe: Shield Synthesis for Timed Systems"

Prerequisite

The conda package manager for python

Setup

Navigate to ./Platoon and execute following commands

conda env create -n your_env_name -f conda_env.yml
conda activate your_env_name
pip install -r pip_req.txt

Usage:
Creating an Agent (platoon.py)
First you need to create an environment

gym.make(ENV_NAME, rendermode, numcars, startdist, startspeed, mindist, maxdist, accsteps, rendermode, seed, shield, shield_file)

All of these key word arguments already have default values and can be changed if needed.
rendermode can be set to None, Minimal, Console, Viewer or Console_Viewer.

The weigths of the agent get saved in ./Platoon/weigths 
and checkpoints can be found in ./Platoon/weigths/checkpoints.
The checkpoints can be disabled by not using a callback for the dqnAgent.
 
All the agents have been trained by taking some amount of steps, saving the weights, reloading the weights and then start the training again.  
The first training session should be between 60.000 and 80.000 steps. (here the load_weigths is not needed)
After that the session can be a larger amount of steps but should not be unreasonably large (80.000 - 200.000).  
Larger amount of cars need more training sessions in order to achieve a good performance.

Using an Agent (test_agent.py)
the gym should be initialized with the values numcars, mindist, maxdist, accsteps the agent has been trained on  
startspeed, startdis can be changed, but might create situations where the agent has no way of preventing a crash
rendermode can be set to None, Minimal, Console, Viewer or Console_Viewer

the model, memory and policy need to be set according to the agent  
now the weigths of the agent can be loaded

dqn.load_weights('weights/agent_name')

Pre-trained agents from 2 - 10 cars can be found in ./Platoon/weigths

Environment
the environment can be found in ./Platoon/custom_gym/envs/custom_env_dir and consists of platooning_env.py and car.py

Safestragey

Creating a Safe Strategy

1. open UPPAAL and load the ./safe_stragety/cruise.xml file  
2. edit it however you want,
3. use these two commands in the Verifier in order to save the strategy

   strategy safe = control: A[] distance > 5
   saveStrategy("filename.txt", safe)

    

Parser Usage

In safe_strategy/

python parser.py -create in_file_name out_file_name
python parser.py -test file_name

Using the safestrategy

gym.make(ENV_NAME, rendermode, numcars, startdist, startspeed, mindist, maxdist, accsteps, rendermode, seed, shield, shield_file)

Enable the shield by setting shield to True
shield_file should be the path to the previously created safestrategy