Theory of Evolution of Cognitive Systems

This work develops a formal conceptual model of the evolution of cognitive systems. It treats cognitive architectures as the fundamental units of analysis, distributed within a space of architectures endowed with a probability measure. Such architectures are realized across multiple levels—from individual cognitive systems (as carriers) to collective forms of organization, including science, culture, and institutional structures. Within this space, architectures evolve through selection, reproduction, and innovation, governed by replicator-type dynamics. The model is constructed from a minimal set of assumptions that give rise to a system of dynamical equations and macroscopic observables. In particular, the theory introduces variability (defined as the entropy of the distribution), integration (capturing structural coupling between architectures), and tension, defined as T = I · Φ where (Φ) measures structural incompatibility. These variables provide a link between micro-level selection dynamics and large-scale structural behavior. Phase parameters (Λ) and (Γ) define regimes of system organization, including integrated polymorphism, monoculture, fragmentation, and collapse. Transitions between these regimes are interpreted as architectural phase transitions driven by the accumulation of structural tension under conditions of sufficient variability and selection. The proposed model yields a set of qualitative predictions regarding cognitive evolution, including selective concentration, the reduction of polymorphism, the emergence of innovations at structural boundaries, and recurrent crisis dynamics. By combining selection dynamics with phase-based descriptions of large-scale structure, the theory provides a unified perspective on the evolution of knowledge systems and complex cognitive organizations. Disclosure of AI assistance This work was developed with the assistance of AI language models. The author contributed the core concepts, structure, and critical revision.