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Installation of the Environments

  1. Create an environment (requires Conda installation): We are currently developing our environments using a Linux system.

    Use the following command to create a new Conda environment named cmorl with Python 3.11:

    conda create -n cmorl  python=3.9

    Activate the newly created environment:

    conda activate cmorl
  2. Install dependency packages:

    Install the necessary packages using pip. Make sure you are in the project directory where the setup.py file is located:

    pip install -r requirements.txt
    pip install -e .

Run experiments

To run the experiments, run test script, e.g.,

./train_mujoco

Citation

If you find the repository useful, please cite the study

@article{gu2025safe,
  title={Safe and balanced: A framework for constrained multi-objective reinforcement learning},
  author={Gu, Shangding and Sel, Bilgehan and Ding, Yuhao and Wang, Lu and Lin, Qingwei and Knoll, Alois and Jin, Ming},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2025},
  publisher={IEEE}
}

We thank the contributors from GitHub open source repositories 1, 2, 3, and 4.

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[IEEE TPAMI] A Framework for Constrained Multi-Objective Reinforcement Learning

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