Package: ReinforcementLearning Type: Package Title: Model-Free Reinforcement Learning Version: 1.0.5 Date: 2020-03-02 Authors@R: c(person("Nicolas", "Proellochs", email="nicolas.proellochs@wi.jlug.de", role=c("aut", "cre")), person("Stefan", "Feuerriegel", email="sfeuerriegel@ethz.ch", role=c("aut"))) Maintainer: Nicolas Proellochs Description: 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) . License: MIT + file LICENSE Depends: R (>= 3.2.0) Imports: ggplot2, hash (>= 2.0), data.table Suggests: testthat, knitr, rmarkdown LazyData: TRUE Encoding: UTF-8 RoxygenNote: 6.1.1 VignetteBuilder: knitr Repository: https://nproellochs.r-universe.dev Date/Publication: 2020-03-02 01:29:53 UTC RemoteUrl: https://github.com/nproellochs/reinforcementlearning RemoteRef: HEAD RemoteSha: b14091a5320dcaf7c10766c0968eb997fe068b6b NeedsCompilation: no Packaged: 2026-07-03 22:11:12 UTC; root Author: Nicolas Proellochs [aut, cre], Stefan Feuerriegel [aut]