Complex Dynamical Rationality Theory

A normative framework defining rationality not as adherence to fixed rules (expected utility maximization, logical consistency) but as the ability to navigate complex, dynamic environments adaptively. It incorporates bounded rationality, ecological rationality, and evolutionary criteria: a rational agent is one that survives, learns, and thrives in its niche, not one that computes optimal choices. The theory rejects universal rational norms; instead, rationality is domain-specific, embodied, and emergent. It is used to design AI, organizational learning, and policy under uncertainty.

Example: “Complex dynamical rationality theory showed that the most successful traders were not those with perfect models but those who adapted their heuristics to market feedback, switching strategies at tipping points.”

Complex Dynamical Rationality

The practical manifestation of adaptive, context-sensitive rationality. It is what humans and organizations actually do when they reason well under complexity: they use simple heuristics, learn from small failures, diversify strategies, and remain sensitive to feedback. Complex Dynamical Rationality is not about being “logical” but about being effective in a world of non-linear dynamics. It is the rationality of evolution: good enough, not optimal.

*Example: “His complex dynamical rationality meant he didn't try to predict the stock market; he followed a simple rule: cut losses at 10%, let winners run, and re-evaluate monthly. It worked better than any forecasting model.”*

Complex Dynamical Rationality Theory by Dumu The Void May 26, 2026