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”.

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