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by svalorzen
2682 days ago
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If you ever feel like trying out the algorithms contained in the book without going to the trouble of reimplementing everything from scratch feel free to come over to https://github.com/Svalorzen/AI-Toolbox. This is a library I have maintained during the past 5 years and implements quite a lot of RL algorithms, and can be used with both C++ and Python. It's very focused on being understandable and having a clear documentation, so I'd love to help you out starting up :) |
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The first one implements some of the more "exotic" temporal difference learning algorithms (Gradient, Emphatic, Direct Variance) with links to the associated papers. It's in Python and heavily documented.
The second one (mdpy) has code for analyzing MDPs (with a particular focus on RL), so you can look at what the solutions to the algorithms might be under linear function approximation. I wrote it when I was trying to get a feel for what the math meant and continue to find it helpful, particularly when I'm dubious about the results of some calculation.