Building Active Inference in Python

Hands-on course to create active inference agents in Python. Learn step-by-step from setup to applications, culminating in a fully functional grid world agent.

Buy $1,000.00

Course curriculum

1. Week 1: Overview & Learning Obj (PDF for You and Claude)
2. Week 1: Exercises (PDF - UPLOAD to Claude)
1. Lab 1.1: Creating Your Working Python Environment (PDF)
2. Lab 1.1: Code (GitHub LInk)
3. Lab 1.1: Exercise - Creating the Environment (EXERCISE)
1. Lab 1.2: What the Graph Looks Like (TXT)
2. Lab 1.2: Code (GitHub Link)
3. Lab 1.2: The Graph as World Model (PDF)
4. Lab 1.2: Exercise - Graph as World Model (EXERCISE)
1. Lab 1.3: Prior Beliefs over Starting States (OVRVW/TXT)
2. Lab 1.3: Exercise - "Where Do I Begin?" (EXERCISE)
1. Lab 1.4: Observation likelihoods - Mapping Hidden States (OVRVW/TXT)
2. Lab 1.4: Exercise - The A Matrix (EXERCISE)
1. Lab 1.5: Transition probabilities (OVRVW/TXT)
2. Lab 1.5: Exercise - The B Matrix (EXERCISE)
1. Lab 1.6: A Forward Pass (OVRVW/TXT)
2. Lab 1.6: Exercise - Generative Model (EXERCISE)
1. Defining Prior Beliefs
1. Belief Updating and Action Selection
1. Adaptive Behavior
1. Testing Your Full Agent
1. Real-World Applications of Active Inference

About this course

$1,000.00
22 lessons
0 hours of video content

Discover your potential, starting today

Enroll today

Themesis Academy

Building Active Inference in Python

Course curriculum

Week 1: Environment and World Structure

Lab 1.1: Test Imports

Lab 1.2: The Graph as a World Model

Lab 1.3: The D Matrix — Where Does the Agent Begin?

Lab 1.4: The A Matrix — What Can the Agent Observe?

Lab 1.5: The B Matrix — How Does the Agent Move?

Lab 1.6: The Generative Model — Putting It All Together

Chapter 2: The Agent and Its Beliefs

Chapter 3: Inference and Action

Chapter 4: Learning and Adaptation

Chapter 5: The Full Agent Loop

Chapter 6: Extensions and Applications

About this course

Discover your potential, starting today