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RIDE Code issues #5

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yZ265519 opened this issue Feb 25, 2023 · 3 comments
Open

RIDE Code issues #5

yZ265519 opened this issue Feb 25, 2023 · 3 comments

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@yZ265519
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I noticed that there is no part of training network in the ride code, only two random networks are directly encoded, which seems to be inconsistent with the original paper, why is that?

@yuanmingqi
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The utilization of random and fixed encoder is inspired by

Seo Y, Chen L, Shin J, et al. State entropy maximization with random encoders for efficient exploration[C]//International Conference on Machine Learning. PMLR, 2021: 9443-9454.

  1. The key insight of RIDE is to use the difference between two consecutive states to encourage exploration, and a fixed encoder can provide fixed representations;
  2. A random and fixed encoder can provide a stable reward space;
  3. It is more efficient and easy to train.

Anyway, you can follow the original implementation or create a new one, which depends on your task.

@yZ265519
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yZ265519 commented Feb 26, 2023 via email

@yuanmingqi
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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.

@yZ265519

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