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.

Versions [faq] 0.1.0, 0.1.1, 0.1.2, 0.1.2.1, 0.1.2.2, 0.1.2.3, 0.1.2.4
Dependencies base (==4.8.*), binary, containers, deepseq, directory, filepath, free, hashable, heredocs, lens, mersenne-random-pure64, monad-loops, MonadRandom, mtl, pretty-show, process, random, rl-satton, stm, 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 2016-09-20T10:40:37Z
Distributions NixOS:0.1.2.4
Executables example
Downloads 3172 total (10 in the last 30 days)
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Status Hackage Matrix CI
Docs not available [build log]
All reported builds failed as of 2016-11-19 [all 3 reports]

Modules

  • Control
    • Monad
      • Control.Monad.Rnd
  • Graphics
    • Graphics.TinyPlot
  • RL
    • RL.DP
    • RL.Imports
    • RL.MC
    • RL.TD
    • RL.TDl
    • RL.Types
    • RL.Utils

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