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Results tagged with gym
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user 74772
For questions about OpenAI's gym library, which provides a set of APIs to access different types of environments to train reinforcement learning agents.
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Getting always the same action on an A2C from stable_baselines3
I have a custom gym environment that computes the agent rewards based on the actions taken on the step method. … Even though when I evaluate the trained model on a new observation I always get the same set of actions.
env = Monitor(gym.make("gym/MyCustomEnvironment-v0", data=data_test), log_dir)
obs, _ = env.reset …
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