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Model-Based Generative Adversarial Imitation Learning

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Model-Based Generative Adversarial Imitation Learning (MGAIL)

Pytorch implementation for "End-to-End Differentiable Adversarial Imitation Learning", by Nir Baram, Oron Anschel, Itai Caspi, Shie Mannor.

Dependencies

Install the required dependencies using the following command:

pip install -r requirements.txt

References

The code is based on the tensorflow implementation: https://github.com/itaicaspi/mgail

Running

Run the following command to train the Mujoco Hopper-v2 environment by imitating an expert trained with SAC or PPO:

python main.py

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