Package: ReinforcementLearning 1.0.5

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>.

Authors:Nicolas Proellochs [aut, cre], Stefan Feuerriegel [aut]

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Bug tracker:https://github.com/nproellochs/reinforcementlearning/issues

On CRAN:

experience-samplingreinforcement-learning

13 exports 67 stars 3.55 score 30 dependencies 1 dependents 213 scripts 370 downloads

Last updated 5 years agofrom:b14091a532. Checks:OK: 1 NOTE: 6. Indexed: yes.

Exports:computePolicyepsilonGreedyActionSelectionexperienceReplaygridworldEnvironmentpolicyrandomActionSelectionReinforcementLearningreplayExperiencesampleExperiencesampleGridSequenceselectEpsilonGreedyActionselectRandomActionstate

Dependencies:clicolorspacedata.tablefansifarverggplot2gluegtablehashisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr