DLR-RM/stable-baselines3

Assert that the VecNormalize wrapper handles the new truncations correctly

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#1,093 建立於 2022年10月4日

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 (2 留言) (0 反應) (0 負責人)Python (6,550 star) (1,407 fork)batch import
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描述

I need to think more about that one, but my guess is that it should not matter much, the scaling is meant to avoid large values and to evolve with the agent performance. Still, we should double check that. Could you open an issue so we don't forget?

Originally posted by @araffin in https://github.com/DLR-RM/stable-baselines3/pull/780#discussion_r985247261

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pythonpytorch
領域
machine learningai
議題類型
research
難度面向新貢獻者的預計實作難度，1 表示很小改動，5 表示專家級工作。
3
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1-3 hours
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stale
清晰度議題是否清楚說明預期改動、驗收標準和下一步。
mostly clear
前置要求
familiarity with VecNormalize wrapperunderstanding of RL truncation vs termination
新手友善度1-100 的估計分數，表示該議題對首次貢獻者的友善程度。
30
研究方向
Investigate the VecNormalize implementation in stable baselines3 to ensure that truncation steps (as opposed to terminal steps) are correctly handled. Review the discussion in PR #780, particularly the comment by @araffin, and examine the relevant source code in vec normalize.py. Look for any potential issues with normalization updates during non terminal transitions and verify that the scaling logic accommodates truncations without bias.