اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدThe Extended Evolutionary Synthesis Facilitates Evolutionary Models of Culture Change
80
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
The Extended Evolutionary Synthesis (EES) is beginning to fulfill the whole promise of Darwinian insight through its extension of evolutionary understanding from the biological domain to include cultural information evolution. Several decades of important foundation-laying work took a social Darwinist approach and exhibited and ecologically-deterministic elements. This is not the case with more recent developments to the evolutionary study of culture, which emphasize non-Darwinian processes such as self-organization, potentiality, and epigenetic change.
قيم البحث
اقرأ أيضاً
How cooperation can evolve between players is an unsolved problem of biology. Here we use Hamiltonian dynamics of models of the Ising type to describe populations of cooperating and defecting players to show that the equilibrium fraction of cooperato
rs is given by the expectation value of a thermal observable akin to a magnetization. We apply the formalism to the Public Goods game with three players, and show that a phase transition between cooperation and defection occurs that is equivalent to a transition in one-dimensional Ising crystals with long-range interactions. We then investigate the effect of punishment on cooperation and find that punishment plays the role of a magnetic field that leads to an alignment between players, thus encouraging cooperation. We suggest that a thermal Hamiltonian picture of the evolution of cooperation can generate other insights about the dynamics of evolving groups by mining the rich literature of critical dynamics in low-dimensional spin systems.
We present new evolutionary synthesis models for Single Stellar Populations covering a wide range in age and metallicity. The most important difference with existing models is the use of NLTE atmosphere models for the hot stars (O, B, WR, post-AGB st
ars, and planetary nebulae) that have an important impact in the stellar clusters ionizing spectra.
The incubation period of a disease is the time between an initiating pathologic event and the onset of symptoms. For typhoid fever, polio, measles, leukemia and many other diseases, the incubation period is highly variable. Some affected people take
much longer than average to show symptoms, leading to a distribution of incubation periods that is right skewed and often approximately lognormal. Although this statistical pattern was discovered more than sixty years ago, it remains an open question to explain its ubiquity. Here we propose an explanation based on evolutionary dynamics on graphs. For simple models of a mutant or pathogen invading a network-structured population of healthy cells, we show that skewed distributions of incubation periods emerge for a wide range of assumptions about invader fitness, competition dynamics, and network structure. The skewness stems from stochastic mechanisms associated with two classic problems in probability theory: the coupon collector and the random walk. Unlike previous explanations that rely crucially on heterogeneity, our results hold even for homogeneous populations. Thus, we predict that two equally healthy individuals subjected to equal doses of equally pathogenic agents may, by chance alone, show remarkably different time courses of disease.
We propose a mathematical model for collective sensing in a population growing in a stochastically varying environment. In the population, individuals use an information channel for sensing the environment, and two channels for signal production and
comprehension to communicate among themselves. We show that existence of such system has a positive effect on population growth, hence can have a positive evolutionary effect. We show that the gain in growth due to the collective sensing is related to information theoretic entities, which can be considered as the information content of this system from the environment. We further show that heterogeneity in communication resulted from network or spatial structure increases growth. We compute the growth rate of a population residing on a lattice and show that growth rate near the maximum noise level in observation or communication, increases exponentially as noise decreases. This exponential effect makes the emergence of collective observation an easy outcome in an evolutionary process. Furthermore, we are able to quantify interesting effects such as accelerated growth, and simplification of decision making due to information amplification by communication. Finally, we show that an amount of noise in representation formation has more disadvantageous effect compared to the same noise in signal production.
We study the stochastic dynamics of evolutionary games, and focus on the so-called `stochastic slowdown effect, previously observed in (Altrock et. al, 2010) for simple evolutionary dynamics. Slowdown here refers to the fact that a beneficial mutatio
n may take longer to fixate than a neutral one. More precisely, the fixation time conditioned on the mutant taking over can show a maximum at intermediate selection strength. We show that this phenomenon is present in the prisoners dilemma, and also discuss counterintuitive slowdown and speedup in coexistence games. In order to establish the microscopic origins of these phenomena, we calculate the average sojourn times. This allows us to identify the transient states which contribute most to the slowdown effect, and enables us to provide an understanding of slowdown in the takeover of a small group of cooperators by defectors: Defection spreads quickly initially, but the final steps to takeover can be delayed substantially. The analysis of coexistence games reveals even more intricate behavior. In small populations, the conditional average fixation time can show multiple extrema as a function of the selection strength, e.g., slowdown, speedup, and slowdown again. We classify two-player games with respect to the possibility to observe non-monotonic behavior of the conditional average fixation time as a function of selection strength.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
