rl-satton: Collection of Reinforcement Learning algorithms

[ bsd3, library, machine-learning, program ] [ Propose Tags ]

rl-satton provides implementation of algorithms, described in the 'Reinforcement Learing: An Introduction' book by Richard S. Satton and Andrew G. Barto. In particular, TD(0), TD(lambda), Q-learing are implemented. Code readability was placed above performance. Usage examples are provided in the ./examples folder.


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Versions [RSS] 0.1.0, 0.1.1, 0.1.2,,,,
Dependencies base (>=4.8 && <5), containers, directory, filepath, hashable, lens, mersenne-random-pure64, monad-loops, MonadRandom, mtl, parsec, pretty-show, process, random, rl-satton, stm, template-haskell, text, time, transformers, unordered-containers [details]
License BSD-3-Clause
Copyright Copyright (c) 2016, Sergey Mironov
Author Sergey Mironov
Maintainer grrwlf@gmail.com
Category Machine Learning
Home page https://github.com/grwlf/rl
Uploaded by SergeyMironov at 2016-10-04T09:06:15Z
Executables example
Downloads 3736 total (8 in the last 30 days)
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Status Docs available [build log]
Last success reported on 2016-10-04 [all 1 reports]