Package: CBT 1.0

Shouri Hu

CBT: Confidence Bound Target Algorithm

The Confidence Bound Target (CBT) algorithm is designed for infinite arms bandit problem. It is shown that CBT algorithm achieves the regret lower bound for general reward distributions. Reference: Hock Peng Chan and Shouri Hu (2018) <arxiv:1805.11793>.

Authors:Hock Peng Chan and Shouri Hu

CBT_1.0.tar.gz
CBT_1.0.zip(r-4.7-any)CBT_1.0.zip(r-4.6-any)
CBT_1.0.tar.gz(r-4.7-any)CBT_1.0.tar.gz(r-4.6-any)
CBT_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CBT/json (API)

# Install 'CBT' in R:
install.packages('CBT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.95 score 1 scripts 244 downloads 9 mentions 6 exports 0 dependencies

Last updated from:bfbed63c53. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK128
source / vignettesOK127
linux-releaseOK131
windows-develOK50
windows-releaseOK58
wasm-releaseOK99

Exports:Ana_CBTCBTCosine_PriorEmp_CBTSine_PriorUniform_Prior

Dependencies:

Readme and manuals

Help Manual

Help pageTopics
Confidence Bound Target (CBT) AlgorithmAna_CBT CBT Cosine_Prior Emp_CBT Sine_Prior Uniform_Prior