Complex Systems·Course
Complex Systems Theory
Complex systems theory: nonlinear dynamics, chaos, network theory, agent-based modeling, critical phenomena, and economic applications
Part of the Mathematics track — finish it for a verifiable diploma →
§ 01 — Orientation
New here?
What you'll be able to do, who this is for, how long it takes, and where to begin.
By the end, you will be able to
- 01Analyze nonlinear dynamics and chaos.
- 02Study networks and their structure.
- 03Build agent-based models.
- 04Understand tipping points and critical phenomena.
- 05See emergence across biology, economics, and society.
Who this is for
How long it takes
- Quick orientationSkim the opening module and the cheatsheet to get the shape of it.~1 h
- Full read-throughRead every article once, in order.~1 h
- Mastery pathRead, take the quizzes, and space out your reviews.~2 weeks
- APA
Stoa. (2026). Complex Systems Theory [Online course]. Stoa. https://stoa.school/course/complex-systems
- MLA
Stoa. “Complex Systems Theory.” Stoa, 2026, https://stoa.school/course/complex-systems.
- Chicago
Stoa. “Complex Systems Theory.” Stoa. Accessed September 1, 2026. https://stoa.school/course/complex-systems.
§ 02 — Curriculum
4 modules.
Each module is a small unit. Most read in sequence — but a determined reader can begin anywhere.
- M IIntroduction to Complex Systems TheoryCore concepts, emergence, and nonlinear dynamics3 articles
18 minBegin → - M IIPopulation Dynamics and Epidemiological ModelsPredator–prey models, SIR models, and spatial dynamics3 articles
18 minBegin → - M IIIAgent-Based Modeling and SimulationCellular automata, ABM models, and emergent behavior in multi-agent systems3 articles
18 minBegin → - M IVCritical Phenomena and Tipping PointsSelf-organized criticality, phase transitions, and early-warning signals3 articles
18 minBegin →
§ 03 — Learning outcomes
4 outcomes.
Analyze attractors, bifurcations, and chaotic behavior in dynamical systems.
Study scale-free networks, the small-world phenomenon, and percolation.
Build agent-based models and analyze emergent behavior.
Understand self-organized criticality, tipping points, and early-warning signals.
§ 04 — Practices