Evolution as computation: integrating self-organization with generalized Darwinism

Generalized Darwinism and self-organization have been positioned as competing frameworks for explaining processes of economic and institutional change. Proponents of each view question the ontological validity and explanatory power of the other. This paper argues that information theory, rooted in modern thermodynamics, offers the potential to integrate these two perspectives in a common and rigorous framework. Both evolution and self-organization can be generalized as computational processes that can be applied to human social phenomena. Under this view, evolution is a process of algorithmic search through a combinatorial design space, while self-organization is the result of non-zero sum gains from information aggregation. Evolution depends on the existence of self-organizing forces, and evolution acts on designs for self-organizing structures. The framework yields insights on the role of agency and the emergence of novelty. The paper concludes that information theory may provide a fundamental ontological basis for economic and institutional evolution.