1,464 research outputs found
Unnatural Selection: A new formal approach to punctuated equilibrium in economic systems
Generalized Darwinian evolutionary theory has emerged as central to the description of economic process (e.g., Aldrich et. al., 2008). Here we demonstrate that, just as Darwinian principles provide necessary, but not sufficient, conditions for understanding the dynamics of social entities, in a similar manner the asymptotic limit theorems of information theory provide another set of necessary conditions that constrain the evolution of socioeconomic process. These latter constraints can, however, easily be formulated as a statistics-like analytic toolbox for the study of empirical data that is consistent with a generalized Darwinism, and this is no small thing
The Evolutionary Unfolding of Complexity
We analyze the population dynamics of a broad class of fitness functions that
exhibit epochal evolution---a dynamical behavior, commonly observed in both
natural and artificial 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 offers an alternative to
current ``landscape'' models of evolutionary optimization. We describe the
population dynamics on the macroscopic level of fitness 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 fitness distribution. While a balance between
selection and mutation maintains a quasistationary distribution of fitness,
individuals diffuse randomly through selectively neutral subbasins in genotype
space. Sudden innovations occur when, through this diffusion, a genotypic
portal is discovered that connects to a new subbasin of higher fitness
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 clarifies how
frozen accidents and the resulting phenotypic constraints guide the evolution
to higher complexity.Comment: 28 pages, 5 figure
Fitness and entropy production in a cell population dynamics with epigenetic phenotype switching
Motivated by recent understandings in the stochastic natures of gene
expression, biochemical signaling, and spontaneous reversible epigenetic
switchings, we study a simple deterministic cell population dynamics in which
subpopulations grow with different rates and individual cells can
bi-directionally switch between a small number of different epigenetic
phenotypes. Two theories in the past, the population dynamics and
thermodynamics of master equations, separatedly defined two important concepts
in mathematical terms: the {\em fitness} in the former and the (non-adiabatic)
{\em entropy production} in the latter. Both play important roles in the
evolution of the cell population dynamics. The switching sustains the
variations among the subpopulation growth thus continuous natural selection. As
a form of Price's equation, the fitness increases with () natural selection
through variations and a positive covariance between the per capita
growth and switching, which represents a Lamarchian-like behavior. A negative
covariance balances the natural selection in a fitness steady state | "the red
queen" scenario. At the same time the growth keeps the proportions of
subpopulations away from the "intrinsic" switching equilibrium of individual
cells, thus leads to a continous entropy production. A covariance, between the
per capita growth rate and the "chemical potential" of subpopulation,
counter-acts the entropy production. Analytical results are obtained for the
limiting cases of growth dominating switching and vice versa.Comment: 16 page
Multigame Effect in Finite Populations Induces Strategy Linkage Between Two Games
Evolutionary game dynamics with two 2-strategy games in a finite population
has been investigated in this study. Traditionally, frequency-dependent
evolutionary dynamics are modeled by deterministic replicator dynamics under
the assumption that the population size is infinite. However, in reality,
population sizes are finite. Recently, stochastic processes in finite
populations have been introduced into evolutionary games in order to study
finite size effects in evolutionary game dynamics. However, most of these
studies focus on populations playing only single games. In this study, we
investigate a finite population with two games and show that a finite
population playing two games tends to evolve toward a specific direction to
form particular linkages between the strategies of the two games
Darwinism, probability and complexity : market-based organizational transformation and change explained through the theories of evolution
The study of transformation and change is one of the most important areas of social science research. This paper synthesizes and critically reviews the emerging traditions in the study of change dynamics. Three mainstream theories of evolution are introduced to explain change: the Darwinian concept of survival of the fittest, the Probability model and the Complexity approach. The literature review provides a basis for development of research questions that search for a more comprehensive understanding of organizational change. The paper concludes by arguing for the development of a complementary research tradition, which combines an evolutionary and organizational analysis of transformation and change
The Evolution of Coordination under Inertia
This paper models the phenomenon of inertia driven by individual strategy switching costs in a stochastic evolutionary context. Kandori, Mailath, and Rob's (1993) model of a finite population of agents repeatedly playing a 2x2 symmetric coordination game is extended to allow for such inertia. Taking noise to the limit, a number of new short- to medium-run equilibria emerge, centred around the mixed-strategy equilibrium. Thus, unusually, an evolutionary model is seen to provide some justification for the controversial concept of mixed-strategy equilibrium. However, Kandori, Mailath, and Rob's long-run selection of the risk-dominant equilibrium continues to hold, both under fixed-rate mutations and under state-dependent mutations driven by stochastic switching costs. The key to this is the satisfaction of Blume's (1999) "skew-symmetry" of the noise process, which is shown to be crucial even under simultaneous strategy revisions. In fact, the presence of the new short-run equilibria can under certain conditions serve to reduce the expected waiting time before the risk-dominant equilibrium is reached - an instance of Ellison's (2000) idea that evolution is more rapid when it can proceed via a series of small "steps" between extremes. This suggests inertia to be a surprisingly efficient phenomenon, and also serves to moderate the force of the Ellison (1993) critique of excessively long transition times in models with vanishing noise.
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