Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Replacing RNN with Self-Attention Mechanism #21

Open
rabaur opened this issue Nov 17, 2020 · 2 comments
Open

Replacing RNN with Self-Attention Mechanism #21

rabaur opened this issue Nov 17, 2020 · 2 comments

Comments

@rabaur
Copy link

rabaur commented Nov 17, 2020

Dear David Ha, dear Jürgen Schmidhuber

Thank for this inspirational blog-post. I have stumbled upon your paper while researching for my BSc thesis. It is concerned with training agents to navigate in complex buildings. As you know, navigation is a very complex task where memory is great importance.

Given the complexity of the task and the promising results of self-attention, I was wondering if you have considered exchanging the RNN with self-attention mechanism. I reckon that this would make the memory model more powerful while being computationally less expensive.

Thank you for your considerations,
Raphaël Baur, BSc Student ETH Zürich

@hardmaru
Copy link
Contributor

Hi Raphaël,

In later work, I've generally kept the RNN, but replaced the latent space bottleneck with other types of bottlenecks related to self-attention.

For example:

  1. Inattentional Blindness bottleneck: https://attentionagent.github.io/

  2. Screen shuffling bottleneck: https://attentionneuron.github.io/

Cheers.

@rabaur
Copy link
Author

rabaur commented Sep 14, 2021

This is very insightful, thank you so much for your answer!

@rabaur rabaur closed this as completed Sep 14, 2021
@worldmodels worldmodels reopened this Sep 16, 2021
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants