pymdps 0.1.1

pymdps is a Python package for working with Markov Decision Processes (MDPs) and

Partially Observable Markov Decision Processes (POMDPs). It is meant to be fast, understandable, and easy to use.

Keywords: MDP,POMDP,Markov Decision Processes,AI,Reinforcement Learning Home-Page: https://github.com/duncaneddy/pymdps Author: Duncan Eddy <[e-mail]> Author-email: Duncan Eddy <[e-mail]> Maintainer-email: Duncan Eddy <[e-mail]> License: MIT Requires-Python: >=3.9 Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM Project-URL: Documentation, https://duncaneddy.github.io/pymdps/ Project-URL: Repository, https://github.com/duncaneddy/pymdps Project-URL: Issues, https://github.com/duncaneddy/pymdps/pulls

# PyMDPs

PyMDPs is a Python library for working with Markov Decision Processes (MDPs) and other related models like Partially Observable MDPs (POMDPs). It is designed to be easy to use and flexible, with a focus on providing a clean and intuitive API for defining and solving MDPs.

## Features

• Simple API: PyMDPs provides a simple and intuitive API for defining MDPs and solving them using a variety of algorithms.

• Modular Design: PyMDPs is designed to be modular and extensible, making it easy to add new algorithms and features.

• Well-Documented: PyMDPs comes with comprehensive documentation and examples to help you get started quickly.

• Open Source: PyMDPs is open source and released under the MIT license, so you are free to use it for any purpose.

## Getting Started

For an introduction to PyMDPs and a guide on how to get started, check out the [Getting Started](getting_started/index.md) page.

To quickly install PyMDPs, you can use pip:

`bash pip install pymdps `

## Documentation

The documentation is divided into the following sections:

• [Getting Started](getting_started/index.md): A guide to getting started with PyMDPs. This section covers installation instructions and a simple example of creating and solving an MDP.

• [API Reference](api_reference/index.md): The complete API reference for PyMDPs, including detailed descriptions of all classes and functions.

• [Reference](reference/index.md): This contains detailed information about the problems, algorithms, models, and other concepts used in PyMDPs.