pymdps is a Python package for working with Markov Decision Processes (MDPs) and
Project description
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 <duncan.eddy@gmail.com> Author-email: Duncan Eddy <duncan.eddy@gmail.com> Maintainer-email: Duncan Eddy <duncan.eddy@gmail.com> 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.
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