Welcome to pymdp’s documentation!
pymdp is a Python package for simulating active inference agents in
discrete space and time, using partially-observed Markov Decision Processes
(POMDPs) as a generative model class. The package is designed to be modular and flexible, to
enable users to design and simulate bespoke active inference models with varying levels of
specificity to a given task.
For a theoretical overview of active inference and the motivations for developing this package, please see our companion paper: “pymdp: A Python library for active inference in discrete state spaces”.