Analytical Results for Individual and Group Selection of Any Intensity

The idea of evolutionary game theory is to relate the payoff of a game to reproductive success (= fitness). An underlying assumption in most models is that fitness is a linear function of the payoff. For stochastic evolutionary dynamics in finite populations, this leads to analytical results in the limit of weak selection, where the game has a small effect on overall fitness. But this linear function makes the analysis of strong selection difficult. Here, we show that analytical results can be obtained for any intensity of selection, if fitness is defined as an exponential function of payoff. This approach also works for group selection (= multi-level selection). We discuss the difference between our approach and that of inclusive fitness theory

Evolution of norms in a multi-level selection model of conflict and cooperation

We investigate the evolution of social norms in a game theoretical model of multi-level selection and mutation. Cooperation is modelled at the lower level of selection by means of a social dilemma in the context of indirect reciprocity, whereas at the higher level of selection conflict is introduced via different mechanisms. The model allows the emergence of norms requiring high levels of cognition. Results show that natural selection and mutation lead to the emergence of a robust yet simple social norm, which we call stern-judging. Stern-judging is compatible with expectations that anthropologists have regarding the Pleistocene hunter gatherer communities. Perhaps surprisingly, it also fits very well recent studies of the behaviour of reputation-based e-trading. Under stern-judging, helping a good individual or refusing help to a bad individual leads to a good reputation, whereas refusing help to a good individual or helping a bad one leads to a bad reputation. The lack of ambiguity of sternjudging, where implacable punishment is compensated by prompt forgiving, supports the idea that simplicity is often associated with evolutionary success. © 2010 by Nova Science Publishers, Inc. All Rights Reserved.SCOPUS: ch.binfo:eu-repo/semantics/publishe

Force-induced desorption of self-avoiding walks on Sierpinski gasket fractals

In this work we investigate force-induced desorption of linear polymers in good solvents in non-homogeneous environment, by applying the model of self-avoiding walk on two- and three-dimensional fractal lattices, obtained as generalization of the Sierpinski gasket fractal. For each of these lattices one of its boundaries represents an adsorbing wall, whereas along one of the fractal edges, not lying in the adsorbing wall, an external force acts on the self-avoiding walk. The hierarchical nature of the lattices under study enables an exact real-space renormalization group treatment, which yields the phase diagram of polymer critical behavior. We show that for this model there is no low-temperature reentrance in the cases of two-dimensional lattices, whereas in all studied three-dimensional cases the force-temperature dependance is reentrant. We also find that in all cases the force-induced desorption transition is of first order