Skip to content
Learning to Imitate Behaviors from Raw Video via Context Translation
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
ablations_code
contrib
docker
docs
examples
gym
nets
notebooks
rllab.egg-info
rllab
sandbox
scripts
tests
vendor/mujoco_models
.gitignore
.gitmodules
CHANGELOG.md
LICENSE
README.md
circle.yml
environment.yml
expert_push.pkl
expert_reach.pkl
expert_reacher.pkl
expert_striker.pkl
expert_sweep.pkl
expert_thrower.pkl
experttheano_clean.pkl
experttheano_push.pkl
experttheano_reach.pkl
params.pkl
run_im.py
setup.py
test.sh

README.md

Imitation from Observation

Learning to Imitate Behaviors from Raw Video via Context Translation

[Paper] [Videos]

Environments:

Experiments:

  • Launchers: experiments using our method, baselines, and model trainers
  • Notebooks: Various notebooks for model training, debugging, generating plots, etc.

Docs License Join the chat at https://gitter.im/rllab/rllab

rllab

rllab is a framework for developing and evaluating reinforcement learning algorithms. It includes a wide range of continuous control tasks plus implementations of the following algorithms:

rllab is fully compatible with OpenAI Gym. See here for instructions and examples.

rllab only officially supports Python 3.5+. For an older snapshot of rllab sitting on Python 2, please use the py2 branch.

rllab comes with support for running reinforcement learning experiments on an EC2 cluster, and tools for visualizing the results. See the documentation for details.

The main modules use Theano as the underlying framework, and we have support for TensorFlow under sandbox/rocky/tf.

Documentation

Documentation is available online: https://rllab.readthedocs.org/en/latest/.

Citing rllab

If you use rllab for academic research, you are highly encouraged to cite the following paper:

Credits

rllab was originally developed by Rocky Duan (UC Berkeley / OpenAI), Peter Chen (UC Berkeley), Rein Houthooft (UC Berkeley / OpenAI), John Schulman (UC Berkeley / OpenAI), and Pieter Abbeel (UC Berkeley / OpenAI). The library is continued to be jointly developed by people at OpenAI and UC Berkeley.

Slides

Slides presented at ICML 2016: https://www.dropbox.com/s/rqtpp1jv2jtzxeg/ICML2016_benchmarking_slides.pdf?dl=0

You can’t perform that action at this time.
You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session.