ReinforcementLearning: Model-Free Reinforcement Learning

Performs model-free reinforcement learning in R. This implementation enables the learning of an optimal policy based on sample sequences consisting of states, actions and rewards. In addition, it supplies multiple predefined reinforcement learning algorithms, such as experience replay.

Version: 1.0.1
Depends: R (≥ 3.2.0)
Imports: ggplot2, hash (≥ 2.0), data.table
Suggests: testthat, knitr, rmarkdown
Published: 2017-06-19
Author: Nicolas Proellochs [aut, cre], Stefan Feuerriegel [aut]
Maintainer: Nicolas Proellochs <nicolas.proellochs at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: ReinforcementLearning results


Reference manual: ReinforcementLearning.pdf
Vignettes: Reinforcement Learning in R
Package source: ReinforcementLearning_1.0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: ReinforcementLearning_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: ReinforcementLearning_1.0.1.tgz
Old sources: ReinforcementLearning archive


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