Maja Machine Learning Framework
The Maja Machine Learning Framework (MMLF) is a general framework for problems in the domain of Reinforcement Learning (RL). It provides a set of RL related algorithms and a set of benchmark domains. Furthermore it is easily extensible and allows to automate benchmarking of different agents.
Among the RL algorithms are TD(lambda), DYNA-TD, CMA-ES, Fitted R-Max, and Monte-Carlo learning. MMLF contains different variants of the maze-world and pole-balancing problem class as well as the mountain-car testbed.
Further documentation is available under http://mmlf.sourceforge.net/
Contact the mailing list MMLF-support@lists.sourceforge.net if you have any questions.
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Release files for mmlf 1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| mmlf-1.0.zip | 3.2 MB | Details |
Release files / mmlf-1.0.zip
| Download URL | mmlf-1.0.zip |
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| Size | 3.2 MB |
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