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Other tools for developing / comparing RL algorithms: * Burlap (from Brown-UMBC) https://github.com/jmacglashan/burlap https://github.com/jmacglashan/burlap *
by jlas 10y ago
Other tools for developing / comparing RL algorithms:
* Burlap (from Brown-UMBC) https://github.com/jmacglashan/burlap https://github.com/jmacglashan/burlap
* RL Glue http://glue.rl-community.org/wiki/Main_Page http://glue.rl-community.org/wiki/Main_Page
Also looks like some of the challenges come from ALE: https://github.com/mgbellemare/Arcade-Learning-Environment https://github.com/mgbellemare/Arcade-Learning-Environment
- nrmn 10y agoPLE as well! https://github.com/ntasfi/PyGame-Learning-Environment https://github.com/ntasfi/PyGame-Learning-Environment (disclaimer I'm the author)
- gwern 10y agoUnfortunately RL Glue is not nearly as good as it looks or sounds. I was thinking about using it to solve some problems I have (for example, I was interested in modeling embryo selection for complex traits as a POMPD to see what the optimal approaches might be rather than settling for a simple calculation as I did in http://www.gwern.net/Embryo%20selection http://www.gwern.net/Embryo%20selection ), but the project is abandoned, and while it implements an interface/IPC glue, there are few implementations of any interesting environments or useful agents, so you would wind up writing everything yourself anyway. Once I got the simple tabular agent example working, I went looking at the more complex ones and was quite disappointed. From the description in OP, it already far exceeds RL Glue's usefulness.