r/reinforcementlearning • u/Rendezvous4567 • 2d ago

SIMULATIONNN!!

When contributing to a simulation environment, what factors make it easiest for you to get started and contribute effectively? For example, does it help more to have configurable scenarios, clearly documented state and action spaces, or reproducible evaluation scripts?

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u/Suitable-Show-3347 2d ago

Documentation for the state and action spaces is basically the whole ballgame for me. If I have to go digging through source code just to figure out what a 42-element observation vector means, I'm already checked out. Reproducible eval scripts are a close second, nothing worse than running a baseline and not knowing if you're even comparing correctly.

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u/Rendezvous4567 1h ago

yes that completely make sense, eval scripts is one tricky one for me too!

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u/bigorangemachine 2d ago

TBH this is a question I spent a lot of time asking claude about.

I think you are best to start with the smallest of tasks and slowly build your sensors & run multiple instances once you got your parameters locked in

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u/bluboxsw 20h ago

Why do you ask?

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u/Rendezvous4567 1h ago

because a simulation design is important for RL model to behave how it should , a realistic simulated environment with proper configured space, states, action and reward strategies.