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This is a very simple project for tabular reinforcement learning (TabulaRL) that I wrote during my PhD studies.
There are already several great open source packages for reinforcement learning, including:
Out of these, it looks like OpenAI Gym is currently the most promising... if I was starting this all again maybe I would have focused my attention here!
That said, I found that for studying simple tabular RL problems these frameworks were all a little bit of overkill.
If you are experimenting with small, simple, tabular MDPs or just learning about RL for the first time it can be nice to have a really simple bit of code to get started.
The nice thing about this code instead of something like Gym is:
All written in simple Python+Numpy, no complicated dependencies beyond standard Anaconda
Very few lines of code, potentially more accessible to novice programmers.
Focus on very simple problems.
But the main reason I'm putting this code up is so that people can more easily implement/verify some of the ideas in some of my papers!