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AI-CPS-SIEGE

Artifact evaluation for TSE submission "SIEGE: A Semantics-Guided Safety Enhancement Framework for AI-enabled Cyber-Physical Systems" by Jiayang Song, Xuan Xie and Lei Ma.

System requirement

Code Structure

The directory AI-CPS-SIEGE/ contains 5 sub-directory ACC/, AFC/, APV/, BBC/, and LKA/. Each of them stores the indicated AI-CPS introduced in Experimental Systems, and we take the directory LKA/ as an example.

LKA/ involves the following sub-directories:

  • abstraction/ stores the scripts for the abstraction process.

  • data_generation/ has one sub-directory: generated_date/.This folder generated_date/ stores the simulated data from each DRL controller. And the script LKA_data_generator.mlx initiates the simulation with selected controllers.

  • DRL_training/ stores the scripts for training new DRL agents for the AI-CPS. This folder contains three scripts, LKA_DDPG_training.mlx, LKA_TD3_training.mlx, LKA_SAC_training.mlx, and one sub-directory trained_agent/. The former scripts train DRL agents with specified algorithms, and the latter collected the pre-trained agents.

  • ensemble/ stores the script LKA_AC_ensemble_training.mlx for training the "higher-level" coordinator DRL agent. And a sub-directory trained_agent/ contains the pre-trained coordinator agents.

  • evaluation/ stores the.mat files that record the evaluation results for each type of controller.

  • model/ stores all the Simulink .slx that are used for system simulations.

Installation

  • Clone the repository git clone https://github.com/sjywdxs/AI-CPS-SIEGE.git
  • It is recommended to install the latest version of MATLAB to handle the simulink models with reinforcement learning controllers.

How to run the script

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