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Christine Taylor

Publications and source records attributed to Christine Taylor.

7 recordsLinked to original sources
PubMed2006

Evolutionary game dynamics in finite populations with strong selection and weak mutation.

We study stochastic game dynamics in finite populations. To this end we extend the classical Moran process to incorporate frequency-dependent selection and mutation. For 2 x 2 games, we give a complete analysis of the long-run behavior when mutation rates are small. For 3 x 3 coordination games, we provide a simple rule to determine which strategy will be selected in large populations. The expected motion in our model resembles the standard replicator dynamics when the population is large, but is qualitatively different when the population is small. Our analysis shows that even in large finite populations the behavior of a replicator-like system can be different from that of the standard replicator dynamics. As an application, we consider selective language dynamics. We determine which language will be spoken in finite large populations. The results have an intuitive interpretation but would not be expected from an analysis of the replicator dynamics.

Biological Evolution↗
PubMed2006

A symmetry of fixation times in evoultionary dynamics.

In this paper, we show that for evolutionary dynamics between two types that can be described by a Moran process, the conditional fixation time of either type is the same irrespective of the selective scenario. With frequency dependent selection between two strategies A and B of an evolutionary game, regardless of whether A dominates B, A and B are best replies to themselves, or A and B are best replies to each other, the conditional fixation times of a single A and a single B mutant are identical. This does not hold for Wright-Fisher models, nor when the mutants start from multiple copies.

Animals↗
PubMed2006

Evolutionary game dynamics with non-uniform interaction rates.

The classical setting of evolutionary game theory, the replicator equation, assumes uniform interaction rates. The rate at which individuals meet and interact is independent of their strategies. Here we extend this framework by allowing the interaction rates to depend on the strategies. This extension leads to non-linear fitness functions. We show that a strict Nash equilibrium remains uninvadable for non-uniform interaction rates, but the conditions for evolutionary stability need to be modified. We analyze all games between two strategies. If the two strategies coexist or exclude each other, then the evolutionary dynamics do not change qualitatively, only the location of the equilibrium point changes. If, however, one strategy dominates the other in the classical setting, then the introduction of non-uniform interaction rates can lead to a pair of interior equilibria. For the Prisoner's Dilemma, non-uniform interaction rates allow the coexistence between cooperators and defectors. For the snowdrift game, non-uniform interaction rates change the equilibrium frequency of cooperators.

Biological Evolution↗
PubMed2004

Emergence of cooperation and evolutionary stability in finite populations.

To explain the evolution of cooperation by natural selection has been a major goal of biologists since Darwin. Cooperators help others at a cost to themselves, while defectors receive the benefits of altruism without providing any help in return. The standard game dynamical formulation is the 'Prisoner's Dilemma', in which two players have a choice between cooperation and defection. In the repeated game, cooperators using direct reciprocity cannot be exploited by defectors, but it is unclear how such cooperators can arise in the first place. In general, defectors are stable against invasion by cooperators. This understanding is based on traditional concepts of evolutionary stability and dynamics in infinite populations. Here we study evolutionary game dynamics in finite populations. We show that a single cooperator using a strategy like 'tit-for-tat' can invade a population of defectors with a probability that corresponds to a net selective advantage. We specify the conditions required for natural selection to favour the emergence of cooperation and define evolutionary stability in finite populations.

Biological Evolution↗
PubMed2004

Evolutionary game dynamics in finite populations.

We introduce a model of stochastic evolutionary game dynamics in finite populations which is similar to the familiar replicator dynamics for infinite populations. Our focus is on the conditions for selection favoring the invasion and/or fixation of new phenotypes. For infinite populations, there are three generic selection scenarios describing evolutionary game dynamics among two strategies. For finite populations, there are eight selection scenarios. For a fixed payoff matrix a number of these scenarios can occur for different population sizes. We discuss several examples with unexpected behavior.

Biological Evolution↗
PubMed2002

Mechanisms underlying maintenance of smooth muscle cell quiescence in rat aorta: role of the cyclin dependent kinases and their inhibitors.

OBJECTIVE: We sought to understand why smooth muscle cell proliferation is effectively repressed in intact rat aortic tissue. METHODS: Quiescent isolated rat aortic smooth muscle cells and segments of intact rat aorta were stimulated with 10% serum and the time course of expression and activity of proteins involved in cell cycle control were determined. RESULTS: After serum stimulation, smooth muscle cells in intact aortic tissue exhibit no proliferation, whereas isolated cells entered S phase 14-16 h later. Activation of ERKs 1 and 2, and induction of cyclin D1 occurred both in isolated cells and aortic tissue. Regulation of Cdk4, cyclin E and Cdk2 protein levels was also not different. Levels of the cyclin-dependent kinase inhibitors (CKIs), p16 and p27, were initially high in quiescent isolated cells and tissue; levels were downregulated by serum in isolated cells but not in aortic tissue. Cyclin D1/Cdk4, and cyclin E/Cdk2 kinases were active before S phase entry in isolated cells, but remained inactive in aortic tissue. CONCLUSIONS: Cell cycle entry is prevented in aortic tissue, and this is associated with an inability to downregulate p16 and p27 CKIs, and therefore to activate cyclin D1 and cyclin E associated kinase activities.

Animals↗