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DITTO: Offline Imitation Learning with World Models

Link to paper

Getting Started

Code is currently considered pre-release, and not ready for significant external use. Beware.

To get started quickly, download and unpack the following tarball:

wget https://www.robots.ox.ac.uk/\~bdemoss/testdata.tar.gz

which includes 10 episodes from a strong PPO agent playing Breakout, as well as a converged world model for Breakout. The episodes should be put in their own directory, WM can be wherever.

Adjust the directories in src/config/test_config.yaml to match these directories (command line passing coming). Then, run main.py - then let the debugging begin.

Other

Known numpy dependency bug, should be fixed with new gym envs from Farama coming Feb 23:

noops = self.unwrapped.np_random.integers(1, self.noop_max + 1)

is the secret problem

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