The project is under active development

Baconian: Boosting the model-based reinforcement learning

Baconian [beˈkonin] is a toolbox for model-based reinforcement learning with user-friendly experiment setting-up, logging and visualization modules developed by CAP. We aim to develop a flexible, re-usable and modularized framework that can allow the user's to easily set-up a model-based rl experiments by reuse modules we offered.

Release news:

• 2019.4.26 We just finished our demo paper to introduce Baconian: https://arxiv.org/abs/1904.10762
• 2019.4.4 Released the v0.1.4. Added benchmark results on DDPG, visualization of results will be given later. Fixed some bugs.
• 2019.3.24 Released the v0.1.3. Added GP dynamics, fix some bugs.
• 2019.3.23 Released the v0.1.2. Added linear dynamics, iLQR, LQR methods.

For previous news, please go here

Documentation

Documentation is available at http://baconian-public.readthedocs.io/

TODO and Road Map

Currently, the project is under activate development. We are working towards a stable 1.0 version. Details of the road map and future plans will be released as soon as possible.

Currently we are working on

• Visualization module
• Simplify flow module
• State-of-art model-based algorithms: PILCO, GPS etc.
• Latent-space method supporting.

Acknowledgement

Thanks to the following open-source projects:

• garage: https://github.com/rlworkgroup/garage
• rllab: https://github.com/rll/rllab
• baselines: https://github.com/openai/baselines
• gym: https://github.com/openai/gym
• trpo: https://github.com/pat-coady/trpo
• PILCO: https://github.com/nrontsis/PILCO

Citing Baconian

If you find Baconian is useful for your research, please consider cite our demo paper here:

@article{
linsen2019baconian, 
title={Baconian: A Unified Opensource Framework for Model-Based Reinforcement Learning}, 
author={Linsen, Dong and Guanyu, Gao and Yuanlong, Li and Yonggang, Wen}, 
journal={arXiv preprint arXiv:1904.10762},
year={2019} 
}

Report an issue

If you find any bugs on issues during your usage of the package, please open an issue or send an email to me ([email protected]) with detailed information. I appreciate your help!