The Evolutionary Unfolding of Complexity

We analyze the population dynamics of a broad class of tness functions that exhibit epochal evolution|a dynamical behavior, commonly observed in both natural and arti cial evolutionary processes, in which long periods of stasis in an evolving population are punctuated by sudden bursts of change. Our approach| statistical dynamics|combines methods from both statistical mechanics and dynamical systems theory in a way that o ers an alternative to current \landscape" models of evolutionary optimization. We describe the population dynamics on the macroscopic level of tness classes or phenotype subbasins, while averaging out the genotypic variation that is consistent with a macroscopic state. Metastability in epochal evolution occurs solely at the macroscopic level of the tness distribution. While a balance between selection and mutation maintains a quasistationary distribution of tness, individuals di use randomly through selectively neutral subbasins in genotype space. Sudden innovations occur when, through this di usion, a genotypic portal is discovered that connects to a new subbasin of higher tness genotypes. In this way, we identify innovations with the unfolding and stabilization of a new dimension in the macroscopic state space. The architectural view of subbasins and portals in genotype space clari es how frozen accidents and the resulting phenotypic constraints guide the evolution to higher complexity.