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The seed function was designed to interface with Gym environments that may require setting a seed.
Every mushroom environment uses the default NumPy random seed generator.
Probably, it's a good idea to add a more informative message in the agent class or to set the NumPy seed there.
However, we prefer to set the random seed in the experiment function explicitly, before creating the environment. This is due to the fact that the same seed will affect both the environment and the policy (unless using a torch policy, in which case, also the torch seed must be set).
Describe the bug
I get
NotImplementedError
when I try to set seed on some of the envrionments.To Reproduce
Expected behavior
I expected seed to be set
System information (please complete the following information):
Additional context
Error message I get
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