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This repository was archived by the owner on May 21, 2022. It is now read-only.
I know that Reinforce.jl is not trying to emulate OpenAI gym exactly, but I'm curious behind the reasoning to a couple interface decisions that seem inconsistent with gym's.
First, why doesn't reset!(env) return a state or observation for convenience? From personal experience, when I was using OpenAIGym.jl, reset!(env) was always returning false. This was happening because julia returns the variable on the last line of the function by default, which happened to come from env.done=false. I had to look through the source code to figure out what was happening. Returning a state/observation would be consistent with gym, and would avoid any confusion for new users.
Second, why does step!(env, s, a) return r, s' instead of s',r? This is a minor difference in ordering, but once again, I had an expectation for what step! should return from gym.