PYMDP: The Official Documentation

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Title: PYMDP: The Official Documentation
Category: Website
Skill Level:
Beginner (304)

Description:
This website is the official documentation for pymdp, a Python library for
implementing active inference. Active inference is a computational framework
from neuroscience used to model how intelligent agents—like animals or
sophisticated AI—perceive, act, and learn. The core idea is that these
agents are driven to minimize surprise and uncertainty about their
environment, a concept formalized by the Free Energy Principle.

This documentation is a useful resource for anyone looking to build and
simulate these agents. It provides a comprehensive guide to using pymdp to
create generative models, which are the internal belief systems that agents
use to understand and predict their world. You will learn how to design
agents that can make decisions, update their beliefs based on new
observations, and pursue goals.

The website is organized into several key sections:

Getting Started: This section provides tutorials that walk you through the
basics of setting up your first active inference agent.

API Reference: For more advanced users, this section offers a detailed
reference to all the classes and functions in the pymdp library.

Examples: A collection of real-world examples and case studies that showcase
how pymdp can be used to model specific behaviors and tasks.

Theoretical Background: For those interested in the underlying theory, this
section provides in-depth explanations of active inference and the Free
Energy Principle.

The documentation is written in a clear and accessible style, with plenty of
code examples to help you along the way. Whether you're a student or
researcher, this website will help you get started with pymdp and active
inference.



Link to Resource:
- Welcome to pymdp’s documentation! (https://pymdp-rtd.readthedocs.io/en/latest/)

Tags:
ai (271), machine-learning (272), artificial-intelligence (884), cognitive-science (878), computer-science (875), python (69)

Domain:
ACCESS CSSN (780)

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