A meta-IRL algorithm for mean field games that learns task-conditioned rewards from mixed-type expert trajectories using a latent context variable.
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Meta-Inverse Reinforcement Learning for Mean Field Games via Probabilistic Context Variables
A meta-IRL algorithm for mean field games that learns task-conditioned rewards from mixed-type expert trajectories using a latent context variable.