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I can develop RL agents that can solve pyCMO scenarios
Acceptance Criteria
Given
that it is currently unclear how we can train RL agents in pyCMO
When
we convert pyCMO into an OpenAI Gym environment (or at least make an interface that will make pyCMO behave like a Gym environment
Then
we open up pyCMO to more collaboration and we can leverage a vast repository of RL agents that are compatible with Gym environments
Notes
OpenAI Baselines is a set of high-quality implementations of reinforcement learning algorithms.
Gymnasium is an open source Python library for developing and comparing reinforcement learning algorithms by providing a standard API to communicate between learning algorithms and environments
The text was updated successfully, but these errors were encountered:
Why
As a
User of
pyCMO
I want
to be able to easily train RL agents in
pyCMO
So that
I can develop RL agents that can solve
pyCMO
scenariosAcceptance Criteria
Given
that it is currently unclear how we can train RL agents in
pyCMO
When
we convert
pyCMO
into an OpenAI Gym environment (or at least make an interface that will makepyCMO
behave like a Gym environmentThen
we open up
pyCMO
to more collaboration and we can leverage a vast repository of RL agents that are compatible with Gym environmentsNotes
The text was updated successfully, but these errors were encountered: