nicoguertler / graph_rl

Hierarchical reinforcement learning framework which uses a directed graph to define the hierarchy.
MIT License
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Documentation #1

Open MichalBortkiewicz opened 2 years ago

MichalBortkiewicz commented 2 years ago

Hi!

I really like the idea of defining agent policy as a graph and your implementation seems highly generic. However, it is also quite hard to navigate the method calls without a proper overview/documentation of the code.

Can you maybe provide some additional info about code structure, abstractions and nodes activations/interruptions?

Regards

nicoguertler commented 2 years ago

Hi, thank you for your feedback! I agree that without a documentation it is currently hard to navigate and use the code. While I won't be able to write a full documentation right away I can start adding some material. Here are some things I could work on:

What would you be most interested in?

MichalBortkiewicz commented 2 years ago

Thank you for your response!

From my perspective, documentation for classes and methods is alright.

However, the most confusing part for me was the control flow in the graph during the execution of the policy. I had a difficult time understanding the communication between high-level and low-level policies/nodes. I guess a more detailed diagram (maybe UML) of the communication (with message carriers between the nodes) will be super helpful.

I haven't yet checked running graph_rl on a new environment, but a quick tutorial on this would also be nice :)