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- Description:
The Maja Machine Learning Framework (MMLF) is a general framework for problems in the domain of Reinforcement Learning (RL) written in python. 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), CMA-ES, EANT, 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.
- Changes to previous version:
- Experiments can now be invoked from the command line
- Experiments can now be "scripted"
- MMLF Experimenter contains now basic module for statistical hypothesis testing
- MMLF Explorer can now visualize the model that has been learned by an agent
- BibTeX Entry: Download
- Supported Operating Systems: Agnostic
- Data Formats: None
- Tags: Reinforcement Learning, Optimization, Evolution, Toolbox, Neuroevolution
- Archive: download here
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