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Scalable Procedural Content Generation via Transfer Reinforcement Learning

This repository contains the code to run the experiments conducted in our paper as well as re-generate the graphs based on the Replay traces.

To run the experiments, make a python weel of the rust environment:

maturin build --manylinux=off --release

and then install the resulting .whl file.

The experiments can be ran using experiments/pysrc/main.py and the graphs can be generated with experiments/pysrc/plot.py.

The environment implementation is found in envs/linerider. THe rest is mostly glue for Rust <=> Python interaction.

The replay traces to re-generate the graphs or verify can be found in the Github Releases of this repository.

To regenerate the graphs extract the files to a folder called 0exp at the root of the experiment.

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