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Title: Evolutionary models in structured populations
Author: Hadjichrysanthou, C.
ISNI:       0000 0004 2720 6535
Awarding Body: City University
Current Institution: City, University of London
Date of Award: 2012
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Evolutionary dynamics have been traditionally studied in infinitely large homogeneous populations where each individual is equally likely to interact with every other individual. However, real populations are finite and characterised by complex interactions among individuals. In this work, the influence of the population structure on the outcome of the evolutionary process is explored. Through an analytic approach, this study first examines the stochastic evolutionary game dynamics following the update rules of the invasion process, an adaptation of the Moran process, on finite populations represented by three simple graphs; the complete graph, the circle and the star graph. The exact formulae for the fixation probability and the speed of the evolutionary process under different conditions are derived, and the effect of the population structure on each of these quantities is studied. The research then considers to what extent the change of the strategy update rules of the evolutionary dynamics can affect the evolutionary process in structured populations compared to the process in homogeneous well-mixed populations. As an example, the evolutionary game dynamics on the extreme heterogeneous structure of the star graph is studied analytically under different update rules. It is shown that in contrast to homogeneous populations, the choice of the update rules might be crucial for the evolution of a non-homogeneous population. Although an analytic investigation of the process is possible when the contact structure of the population has a simple form, this is usually infeasible on complex structures and the use of various assumptions and approximations is necessary. This work introduces an effective method for the approximation of the evolutionary process in populations with a complex structure. Another component of this research work involves the use of game theory for the modelling of a very common phenomenon in the natural world. The models developed examine the evolution of kleptoparasitic populations, foraging populations in which animals can steal the prey from other animals for their survival. A basic game-theoretical model of kleptoparasitism in an infinite homogeneous well-mixed population is extended to structured populations represented by different graphs. The features of the population structure that might favour the appearance of kleptoparasitic behaviour among animals are addressed. In addition, a game-theoretical model is proposed for the investigation of the ecological conditions that encourage foraging animals to share their prey, a very common behaviour occurring in a wide range of animal species.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QA Mathematics