CRAN/E | ReinforcementLearning

ReinforcementLearning

Model-Free Reinforcement Learning

Installation

About

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. Methodological details can be found in Sutton and Barto (1998) .

Key Metrics

Version 1.0.5
R ≥ 3.2.0
Published 2020-03-02 1517 days ago
Needs compilation? no
License MIT
License File
CRAN checks ReinforcementLearning results

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Maintainer

Maintainer

Nicolas Proellochs

nicolas.proellochs@wi.jlug.de

Authors

Nicolas Proellochs

aut / cre

Stefan Feuerriegel

aut

Material

README
NEWS
Reference manual
Package source

Vignettes

Reinforcement Learning in R

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ReinforcementLearning archive

Depends

R ≥ 3.2.0

Imports

ggplot2
hash ≥ 2.0
data.table

Suggests

testthat
knitr
rmarkdown

Reverse Imports

lazytrade