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:
CBT_1.0.tar.gz
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✨
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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:bfbed63c53. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 100 | ||
| source / vignettes | OK | 116 | ||
| linux-release-x86_64 | OK | 89 | ||
| wasm-release | OK | 82 |
Exports:Ana_CBTCBTCosine_PriorEmp_CBTSine_PriorUniform_Prior
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Confidence Bound Target (CBT) Algorithm | Ana_CBT CBT Cosine_Prior Emp_CBT Sine_Prior Uniform_Prior |