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RLE-Foundation / RLeXplore

RLeXplore provides stable baselines of exploration methods in reinforcement learning, such as intrinsic curiosity module (ICM), random network distillation (RND) and rewarding impact-driven exploration (RIDE).
https://docs.rllte.dev/
MIT License
352 stars 16 forks source link

NGU - need to understand this line #8

Open emrul opened 1 year ago

emrul commented 1 year ago

https://github.com/yuanmingqi/rl-exploration-baselines/blob/35d9496affd7afae13873479e33845a90d3583fd/rlexplore/ngu/ngu.py#L54

Hi in this line we set the same variable twice - should it instead be target_network?

yuanmingqi commented 1 year ago

Dear emrul,

This repo has been merged with a new project: https://github.com/RLE-Foundation/Hsuanwu

We provide a more implementation in this new project.

Use from hsuanwu.xplore.reward import NGU

Thank you!

yuanmingqi commented 7 months ago

Hello! We've published a big update that provides more reasonable implementations of these intrinsic rewrads.

If you have any other questions, please don't hesitate to ask here.

@emrul