thompson
Thompson is Python package to evaluate the multi-armed bandit problem. In addition to thompson, Upper Confidence Bound (UCB) algorithm, and randomized results are also implemented.
Science Score: 54.0%
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Low similarity (13.1%) to scientific vocabulary
Keywords
Repository
Thompson is Python package to evaluate the multi-armed bandit problem. In addition to thompson, Upper Confidence Bound (UCB) algorithm, and randomized results are also implemented.
Basic Info
- Host: GitHub
- Owner: erdogant
- License: mit
- Language: Python
- Default Branch: master
- Homepage: https://erdogant.github.io/thompson
- Size: 5.81 MB
Statistics
- Stars: 2
- Watchers: 1
- Forks: 2
- Open Issues: 0
- Releases: 3
Topics
Metadata Files
README.md
Multi-armed bandit
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Thompsonis Python package to evaluate the multi-armed bandit problem. In addition to thompson, Upper Confidence Bound (UCB) algorithm, and randomized results are also implemented. The thompson package implements three algorithms for solving the multi-armed bandit problem:
Thompson Sampling: A Bayesian approach that maintains probability distributions over the expected rewards of each arm and samples from these distributions to select the next arm to pull.
Upper Confidence Bound (UCB): A deterministic algorithm that selects arms based on their estimated rewards and the uncertainty in those estimates.
Randomized Sampling: A baseline method that randomly selects arms without considering their past performance.
The multi-armed bandit problem is a classic reinforcement learning problem that exemplifies the exploration-exploitation tradeoff dilemma. In this problem, a fixed limited set of resources must be allocated between competing choices in a way that maximizes expected gain, when each choice's properties are only partially known at the time of allocation.
⭐️ Star this repo if you like it ⭐️
Install thompson from PyPI
bash
pip install thompson
Import thompson package
python
import thompson as th
Documentation pages
On the documentation pages you can find detailed information about the working of the thompson with examples.
Examples
References
- https://en.wikipedia.org/wiki/Multi-armed_bandit
Owner
- Name: Erdogan
- Login: erdogant
- Kind: user
- Location: Den Haag
- Website: https://erdogant.github.io/
- Repositories: 51
- Profile: https://github.com/erdogant
Machine Learning | Statistics | Bayesian | D3js | Visualizations
Citation (CITATION.cff)
# YAML 1.2
---
authors:
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family-names: Taskesen
given-names: Erdogan
orcid: "https://orcid.org/0000-0002-3430-9618"
cff-version: "1.1.0"
date-released: 2020-01-03
keywords:
- "python"
- "bayesian"
- "reinforcement-learning"
- "genetic-algorithm"
- "ucb"
- "multi-armed-bandit"
- "thompson"
- "thompson=algorithm"
license: "MIT"
message: "If you use this software, please cite it using these metadata."
repository-code: "https://erdogant.github.io/thompson"
title: "The multi-armed bandit by Thompson Sampling, UCB-Upper confidence Bound, and randomized sampling."
version: "1.0.0"
...
GitHub Events
Total
- Push event: 9
- Create event: 1
Last Year
- Push event: 9
- Create event: 1
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Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Erdogan Taskesen | 3****t | 24 |
| erdogant | e****t@g****m | 21 |
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Last synced: 6 months ago
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- Total issues: 0
- Total pull requests: 0
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Packages
- Total packages: 1
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Total downloads:
- pypi 72 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 3
- Total maintainers: 1
pypi.org: thompson
The multi-armed bandit by Thompson Sampling, UCB-Upper confidence Bound, and randomized sampling.
- Homepage: https://erdogant.github.io/thompson
- Documentation: https://thompson.readthedocs.io/
- License: MIT License Copyright (c) 2020 Erdogan Taskesen Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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Latest release: 1.1.0
published 10 months ago
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Maintainers (1)
Dependencies
- pipinstallsphinx_rtd_theme *
- pipinstallsphinx_rtd_theme *
- pipinstallmatplotlibnumpypandasseaborn *
- matplotlib *
- numpy *
- pandas *