Repository for experimental development of fully autonomous AI for the AI4REALNET project. The work focuses on the development of solutions for multi-agent systems, using the flatland simulation environment.
These packages were developed with python 3.10.11 For package versions see the requirements.txt. In the .vscode folder, a launch.json and settings.json are available to run the different models and perform unittesting.
Example: to run a simple, non-parallelised PPO Training run, set your desired settings in a config file, for example PPO_FNN.yaml and pass it as a command line argument when running ppo.py. Alternatively, use the launch.json to start the script directly under PPO in the run and debug tab. The controller, learner and environment will automatically be setup according to the given configuration.
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.vscode$\rightarrow$ contains examples for launching for model training -
imgs$\rightarrow$ contains images for READMEs -
models$\rightarrow$ contains saved models from training -
run$\rightarrow$ contains model training scripts which can be run either from VSCode or from commandline - more information on how to train models is available in the run README -
src$\rightarrow$ contains relevant source code (algorithms, networks, utility functions, etc.) -
test$\rightarrow$ contains all test funcitons for the sourcecode