A complex adaptive system (CAS) is a system in which many agents interact, adapt based on feedback, and produce emergent behavior that cannot be predicted from the properties of individual agents alone.
Markets are the canonical economic example. No central planner decides prices — they emerge from millions of decentralized decisions. The result is often (not always) efficient allocation.
Key properties
Emergence — system-level behavior arises from local interactions. The aggregate production function is itself an emergent property: it describes an economy-wide relationship that no single firm exhibits.
Feedback loops — agents respond to outcomes, which changes outcomes, which changes agent behavior. This creates path dependence: where you end up depends on where you started.
Adaptation — agents update their strategies based on experience. This makes CAS non-stationary: the system you modeled last year may not behave the same way today.
Why this matters for economics
Standard economic models assume agents with fixed preferences and rational expectations. CAS thinking challenges both:
- Preferences are shaped by experience (endogenous)
- Expectations are formed adaptively, not rationally
This doesn’t mean rational expectations models are wrong — it means they’re a special case of a more general framework. The mental model question is: when is the special case a useful approximation?
Notes
This note is a stub. Explore connections to agent-based models (ABMs), evolutionary game theory, and Hayek’s knowledge problem.