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Active Inference 101: College First Semester — Pedagogical Overview

Vision

This curriculum makes Active Inference accessible to College 1st semester undergraduates through four complementary lenses. Each course covers the same 8 foundational topics but from a different disciplinary perspective.

Tone & Style

Rigorous but accessible. Full mathematical notation. Python/NumPy. Textbook-quality.

Course Map

Course 1: Cognitive Science

Perspective: Mind, brain, behavior

Modules: Systems, Agents, Perception, Cognition, Action, Learning, Communication, Planning

Course 2: Computational Neuroscience

Perspective: Neural circuits & Bayesian brain

Modules: Systems, Agents, Perception, Cognition, Action, Learning, Communication, Planning

Course 3: Mathematical Frameworks

Perspective: Probability, information theory, variational methods

Modules: Systems, Agents, Perception, Cognition, Action, Learning, Communication, Planning

Course 4: Implementation & Simulation

Perspective: Python, pymdp, agent-based modeling

Modules: Systems, Agents, Perception, Cognition, Action, Learning, Communication, Planning

Cross-Course Connections

The same 8 topics appear in every course, building a spiral of understanding. See Cross-Course Map for detailed connections.

How to Use This Curriculum

  • Sequential: Work through one course start to finish.
  • Parallel: Study the same module across all 4 courses.
  • Exploratory: Use the Learning Pathways.