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pyrddlgym-project / pyRDDLGym

A toolkit for auto-generation of OpenAI Gym environments from RDDL description files.
https://pyrddlgym.readthedocs.io/
MIT License
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Do we need the noop_values field in RandomAgent, do we need seed in agent.evaluate()? #252

Closed mike-gimelfarb closed 8 months ago

mike-gimelfarb commented 8 months ago

Discussed in https://github.com/orgs/pyrddlgym-project/discussions/251

Originally posted by **GMMDMDIDEMS** February 23, 2024 I try to achieve reproducible results with the RandomAgent. As I understand it, I should get the same results by specifying a seed, e.g.: ```python agent = RandomAgent( action_space=env.action_space, num_actions=env.max_allowed_actions, seed=42 ) ``` However, if I change the number of episodes I get different different results. Shouldn't the results be identical in every episode? What is the `noop_values` argument in the RandomAgent used for? What is the purpose of the `env seed` that can be assigned in the `def evaluate(...)` method?