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. Methodological details can be found in Sutton and Barto (1998) <ISBN:0262039249>.

Package details

AuthorNicolas Proellochs [aut, cre], Stefan Feuerriegel [aut]
MaintainerNicolas Proellochs <>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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ReinforcementLearning documentation built on March 26, 2020, 7:38 p.m.