Project details for Maja Machine Learning Framework

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Version:
0.9.10
Submitter:
jhm
Author(s):
Jan Hendrik Metzen , Mark Edgington
Posted:
8 April 2011
Last Updated:
8 April 2011
Open Source License:
gpl version 3 or later
Programming Language(s):
python

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Screenshot Maja Machine Learning Framework 0.9.10

by jhm - April 8, 2011, 15:19:56 CET [ Project Homepage BibTeX Download ]

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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:
  • Monitor can now also be configured in MMLF Explorer
  • MMLF Experimenter can now also load results of a prior experiment
  • MMLF Experimenter allows to specify whether world runs should be conducted sequentially or concurrently
  • Added simple LinearMarkovChain environment
  • Added "Writing an experiment" tutorial
  • Removed EANT and CGE from MMLF
BibTeX Entry: Download
Supported Operating Systems: Agnostic
Data Formats: None
Tags: Reinforcement Learning, Optimization, Evolution, Toolbox, Neuroevolution
Archive: download here

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