Package: RLescalation
Type: Package
Title: Optimal Dose Escalation Using Deep Reinforcement Learning
Version: 1.0.3
Authors@R: c(
    person("Kentaro", "Matsuura", , "matsuurakentaro55@gmail.com", 
           role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0001-5262-055X")))
Description: An implementation to compute an optimal dose escalation
        rule using deep reinforcement learning in phase I oncology
        trials (Matsuura et al. (2023)
        <doi:10.1080/10543406.2023.2170402>). The dose escalation rule
        can directly optimize the percentages of correct selection
        (PCS) of the maximum tolerated dose (MTD).
URL: https://github.com/MatsuuraKentaro/RLescalation
BugReports: https://github.com/MatsuuraKentaro/RLescalation/issues
VignetteBuilder: knitr
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Imports: glue, R6, nleqslv, reticulate, stats, utils, zip
Suggests: knitr, rmarkdown
Collate: 'timer.R' 'train_algo.R' 'utils.R' 'escalation_rule.R'
        'rl_dnn_config.R' 'rl_config_set.R' 'compute_rl_scenarios.R'
        'learn_escalation_rule.R' 'setup_python.R' 'zzz.R'
        'simulate_one_trial.R'
Config/pak/sysreqs: libpng-dev python3
Repository: https://matsuurakentaro.r-universe.dev
Date/Publication: 2025-10-07 13:27:23 UTC
RemoteUrl: https://github.com/matsuurakentaro/rlescalation
RemoteRef: HEAD
RemoteSha: 11151fdc2d24da7a5071418f6c64caf323930d81
NeedsCompilation: no
Packaged: 2026-09-20 11:34:51 UTC; root
Author: Kentaro Matsuura [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0001-5262-055X>)
Maintainer: Kentaro Matsuura <matsuurakentaro55@gmail.com>