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low / high of the observation if using the gym_compat module. Some more protections
are enforced now.
numbers are used (in these cases low / max would be mixed up)
the installed open ai gym package meets this requirement (see issue
Add minimal gym version in grid2op after gym_compat module (otherwise it crashes) #185
https://github.com/openai/gym/issues/2166
):waiting for an official fix, grid2op will use the solution proposed there
sampling from spaces.Tuple yields non-random behavior openai/gym#2166 (comment) )