When I'm training a RL model cumulative reward isn't always a true indicator of model performance. It's helpful for me to be able to see how an agent is interacting with the environment to ensure that the training performance is matching my expectation.
Solution
Ideally, I'd like to have a method of visualizing the environments. In particular the Gym, ALE, and Mujoco environments.
Individually, these environments typically expose a render() function of RGB output. Are these methods exposed in the envpool implementation?
Alternatives
None come to mind.
Additional context
Checklist
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Motivation
When I'm training a RL model cumulative reward isn't always a true indicator of model performance. It's helpful for me to be able to see how an agent is interacting with the environment to ensure that the training performance is matching my expectation.
Solution
Ideally, I'd like to have a method of visualizing the environments. In particular the Gym, ALE, and Mujoco environments. Individually, these environments typically expose a render() function of RGB output. Are these methods exposed in the envpool implementation?
Alternatives
None come to mind.
Additional context
Checklist