Project description

duelpy

This is a python package for solving with Preference Based Multi Armed Bandit problems, also known as dueling bandits. Refer to this paper for an overview of the field.

You can compare the implemented algorithms in an experiment by running

python3 -m duelpy.experiments.cli

The experiments are still rather limited. The command-line interface can currently only run regret-based comparisons in a limited set of configurations. Pass the --help flag for more information.

See the documentation for more information about the implemented algorithms.

Project details

These details have not been verified by PyPI

Project links

Homepage

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Release history Release notifications | RSS feed

This version

1.0.0

Mar 31, 2021

0.1.0

Mar 4, 2021

0.0.1

Jun 3, 2020

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

duelpy-1.0.0.tar.gz (105.7 kB view hashes)

Uploaded Mar 31, 2021 Source

Built Distribution

duelpy-1.0.0-py3-none-any.whl (146.5 kB view hashes)

Uploaded Mar 31, 2021 Python 3

Hashes for duelpy-1.0.0.tar.gz

Hashes for duelpy-1.0.0.tar.gz
Algorithm	Hash digest
SHA256	`836627d3ade540bb8405c05a2307d22a0dc68d4205cbc961c44e942b36a487dc`
MD5	`9ffa44814ba865f76d558fa00e0da7cb`
BLAKE2b-256	`ad9f3e8955d0736c4daaaa47d979e30dad8f874f07725137118e1e0471c2934b`

Hashes for duelpy-1.0.0-py3-none-any.whl

Hashes for duelpy-1.0.0-py3-none-any.whl
Algorithm	Hash digest
SHA256	`e8aa35b196d38d34bc9b3db48d08dbb2db547b7bc586575afa0c94206d9d6957`
MD5	`ae0140988dacf1d7a855cc0368c28ca3`
BLAKE2b-256	`b3fa5b7394d338dc749aeb1fee1e131166ceb7964f3c32d0524be51c7aaf84df`