MAB

Multi-armed Bandit set of alogrithms written in Python. The source code can be found on github.

List of MAB implementations

• EpsionGreedy
• BetaTS
• Softmax
• UCB1
• AnnealingSoftmax
• AnnealingEpsionGreedy
• AB testing
• Random Select

Also, the package has trial simulations:

• Motecarlo Simulation

with different types of rewards

• Bernoulli Arms (binary rewards)
• Uniform Arms (uniformly distributed rewards)

How to Install

Two ways to install

- Clone this repository
- pip install mab-hakuinadvisors

How to Use

The best usage example can be found in the file simulation.ipynb

The package can be used as

• A part of another library or software
• API (in progress)
• Theoretical learning by using simulations like in simulation.ipynb or with different types of rewards, algorythms and simulation parameters

Documentation

The full documentation of the library and its functionality can be found here. Note the documentation is not compleated.

Authors

If you have any questions email to Alexey Butyrev, Drew Maniglia