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[NeurIPS 2019] Code for the paper "Learning to Control Self-Assembling Morphologies: A Study of Generalization via Modularity"

Home Page: https://pathak22.github.io/modular-assemblies/

License: Other

Shell 14.59% Python 85.41%
reinforcement-learning artificial-intelligence deep-learning modularity compositionality artificial-creatures assembly morphology

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modular-assemblies's Issues

Question concerning message passing

Hey !

First of all, congratulations for your paper. I really enjoyed reading it, the idea is quite refreshing and I was happy to see I'm not the only one using Unity for RL research. ;)
I do have a (few) technical question(s) however. I have been wondering for several days now how to deal with message passing when learning in mini-batches.

  1. Do you have parallel environments ? If so, there is an important deal of observations preprocessing, right ? I'm talking about the fact that the observations have to be properly lined in order to feed each parent its child message (in the bottom-up case).
  2. Do you consider the message to be part of the output action ? If not, how do you backpropagate through the message sending head? In the appendix, it is written that only the sensory inputs and the action (torque + link/unlink) are considered.

There are a few details that I do not yet completely graps, but I really enjoyed the paper overall.

Thanks a lot for your time !

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