Optimal Adaptive Allocation Using Deep Reinforcement Learning R package RLoptimal version 1.2.2 An implementation to compute an optimal adaptive allocation rule using deep reinforcement learning in a dose-response study (Matsuura et al. (2022) <doi:10.1002/sim.9247>). The adaptive allocation rule can directly optimize a performance metric, such as power, accuracy of the estimated target dose, or mean absolute error over the estimated dose-response curve. Software Imports: DoseFinding, glue, R6, reticulate, stats, utils, zip Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Kentaro Matsuura <matsuurakentaro55@gmail.com> Comprehensive R Archive Network (CRAN) Kentaro Matsuura [aut, cre, cph] (ORCID: <https://orcid.org/0000-0001-5262-055X>), Koji Makiyama [aut, ctb] MIT + file LICENSE (https://CRAN.R-project.org/package=RLoptimal/LICENSE) 2025-10-02 application/tgz https://CRAN.R-project.org/package=RLoptimal doi:10.32614/CRAN.package.RLoptimal en-US