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Stochastic Neural Networks for Hierarchical Reinforcement Learning

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How to run snn4hrl

Stochastic Neural Networks for Hierarchical Reinforcement Learning (snn4hrl) as presented at ICLR by Carlos Florensa, Yan Duan, Pieter Abbeel (https://openreview.net/forum?id=B1oK8aoxe&noteId=B1oK8aoxe)

Checkout the videos!

To reproduce the results, you should first have rllab and Mujoco v1.31 configured. Then, run the following commands in the root folder of rllab:

git submodule add -f https://github.com/florensacc/snn4hrl.git sandbox/snn4hrl
touch sandbox/__init__.py

Then you can do the following:

  • Train a SNN for the Swimmer environment via python sandbox/snn4hrl/runs/train_snn.py
  • Look at the visitation plot including the visitations of every latent code in data/local/egoSwimmer-snn/
  • Train a hierarchical policy on top of that SNN via python sandbox/snn4hrl/runs/hier-snn-egoSwimmer-gather.py

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