Comments (1)
Hi, sorry for the late reply!
We use num_steps_posterior>0
in the sparse reward pointmass experiment, see the config here: https://github.com/katerakelly/oyster/blob/44e20fddf181d8ca3852bdf9b6927d6b8c6f48fc/configs/sparse-point-robot.json
We treated this as a hyperparameter and found that for the dense reward MuJoCo tasks, 0
worked fine. The reason is likely that those tasks don't require coordinated exploration to collect context that has task information. The sparse-reward pointmass task does require coherent exploration, and performing multiple iterations of posterior sampling facilitates that.
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