# PyXAB

> PyXAB - A Python Library for X-Armed Bandit and Online Blackbox Optimization Algorithms

**Wikidata**: [Q127485805](https://www.wikidata.org/wiki/Q127485805)  
**Source**: https://4ort.xyz/entity/pyxab

## Summary
PyXAB is a Python library designed for implementing X-Armed Bandit and online blackbox optimization algorithms, providing tools for sequential decision-making and optimization problems.

## Key Facts
- PyXAB is distributed under the MIT License.
- The library has multiple stable versions, with the latest being 0.1.5 as of March 13, 2023.
- It is classified as free software and a software component.
- The project's documentation is available at https://pyxab.readthedocs.io/en/latest/.
- The source code repository is hosted on GitHub at https://github.com/WilliamLwj/PyXAB.

## FAQs
### Q: What is PyXAB used for?
A: PyXAB is a Python library designed for implementing X-Armed Bandit and online blackbox optimization algorithms.

### Q: What license is PyXAB under?
A: PyXAB is distributed under the MIT License.

### Q: What are the latest versions available?
A: The library has multiple stable versions including 0.0.2 (2023-02-05) through 0.1.5 (2023-03-13).

### Q: Where can I find the source code?
A: The source code repository is hosted on GitHub at https://github.com/WilliamLwj/PyXAB.

## Why It Matters
PyXAB addresses the need for specialized tools in sequential decision-making and optimization problems, particularly in contexts where algorithms must adapt to changing environments or unknown functions. It provides researchers and practitioners with a framework for implementing and testing X-Armed Bandit and online blackbox optimization algorithms, which are essential in fields like machine learning, reinforcement learning, and adaptive systems. The library's open-source nature and structured implementation make it accessible for academic research and practical applications where adaptive decision-making is critical.

## Notable For
- Implementation of X-Armed Bandit algorithms specifically designed for online blackbox optimization.
- Availability of multiple stable versions with incremental updates from February 2023 to March 2023.
- Documentation hosted on Read the Docs platform.
- Open-source nature under the permissive MIT License.
- GitHub repository maintained by the developer WilliamLwj.

## Body
### Overview
PyXAB is a specialized Python library focused on implementing X-Armed Bandit algorithms and online blackbox optimization techniques. The library provides tools for sequential decision-making problems where algorithms must adapt to changing environments or unknown functions.

### Version History
The library has undergone several stable releases:
- 0.0.2 (2023-02-05)
- 0.0.3 (2023-02-12)
- 0.0.4 (2023-02-16)
- 0.0.5 (2023-02-18)
- 0.1.0 (2023-02-22)
- 0.1.1 (2023-03-01)
- 0.1.2 (2023-03-07)
- 0.1.3 (2023-03-09)
- 0.1.4 (2023-03-13)
- 0.1.5 (2023-03-13)

Each version includes incremental improvements and bug fixes, with the most recent release being 0.1.5 as of March 13, 2023.

### Technical Implementation
The library implements algorithms for sequential decision-making problems where the goal is to optimize performance by selecting among multiple options while learning from outcomes. It provides implementations of bandit algorithms that can adapt to changing environments and unknown functions.

### Documentation and Community
PyXAB includes comprehensive documentation available at https://pyxab.readthedocs.io/en/latest/, which serves as a reference for users and developers. The project is maintained through a GitHub repository at https://github.com/WilliamLwj/PyXAB, where users can access the source code, contribute to development, and report issues.

### Licensing and Distribution
PyXAB is distributed under the MIT License, which allows users to freely use, modify, and distribute the software with minimal restrictions. This open-source approach facilitates adoption in both academic research and practical applications.

## References

1. [Release 0.0.2. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.0.2)
2. [Release 0.0.3. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.0.3)
3. [Release 0.0.4. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.0.4)
4. [Release 0.0.5. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.0.5)
5. [Release 0.1.0. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.1.0)
6. [Release 0.1.1. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.1.1)
7. [Release 0.1.2. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.1.2)
8. [Release 0.1.3. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.1.3)
9. [Release 0.1.4. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.1.4)
10. [Release 0.1.5. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.1.5)
11. [Release 0.2.0. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.2.0)
12. [Release 0.2.1. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.2.1)
13. [Release 0.3.0. 2023](https://github.com/WilliamLwj/PyXAB/releases/tag/v0.3.0)
14. [Source](https://api.github.com/repos/WilliamLwj/PyXAB)