RLRom

This module integrates Robust Online Monitoring methods with Reinforcement Learning stuff. The first motivation is testing/monitoring RL models.

Install

Those are needed for building some of the required python modules:

• CMake
• swig

Then run the following:

pip install --upgrade -r requirements.txt 

Running

Run python run_app.py, then open browser.

Features

• Select an environment among a list of supported ones.
• To load a model, choose between
  • Random: random actions
  • Local: Upload model zip files created with stable-baselines-3, then choose one
  • Hugging Face: Fetch the list of models available on Hugging Face, then choose one
• Choose between running with or without human render
• Runs from a list of seeds and store traces
• Compute total rewards
• Plots observation, reward, actions, individually or together of any trace, with flexible layout
• Evaluate (monitor) and plot quantitative and Boolean satisfaction of any Signal Temporal Logic formula (STL)
• Sort runs against STL formula robustness