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  Trajectories used in [How Resilient are Imitation Learning Methods to Sub-Optimal Experts?]()
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  These trajectories are formed by using [Stable Baselines](https://stable-baselines.readthedocs.io/en/master/).
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- Each file is a dict of a set of trajectories with the following keys:
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- * actions: the action in the given timestemp `t`
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- * obs: current state in the given timestemp `t`
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- * rewards: reward retrieved after the action in the given timestemp `t`
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  * episode_returns: The aggregated reward of each episode (each file consists of 5000 runs)
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  * episode_Starts: Whether that `obs` is the first state of an episode (boolean list).
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  Trajectories used in [How Resilient are Imitation Learning Methods to Sub-Optimal Experts?]()
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  These trajectories are formed by using [Stable Baselines](https://stable-baselines.readthedocs.io/en/master/).
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+ Each file is a dictionary of a set of trajectories with the following keys:
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+ * actions: the action in the given timestamp `t`
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+ * obs: current state in the given timestamp `t`
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+ * rewards: reward retrieved after the action in the given timestamp `t`
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  * episode_returns: The aggregated reward of each episode (each file consists of 5000 runs)
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  * episode_Starts: Whether that `obs` is the first state of an episode (boolean list).
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