Mathematical modelling approach to collective decision-making
- Datum: 2017-04-07 kl 13:15
- Plats: Siegbahnsalen, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala
- Doktorand: Zabzina, Natalia
- Om avhandlingen
- Arrangör: Tillämpad matematik och statistik
- Kontaktperson: Zabzina, Natalia
In everyday situations individuals make decisions. For example, a tourist usually chooses a crowded or recommended restaurant to have dinner. In this thesis, we use a generic experimentally validated model of positive feedback to study collective decision-making.
In everyday situations individuals make decisions. For example, a tourist usually chooses a crowded or recommended restaurant to have dinner. Perhaps it is an individual decision, but the observed pattern of decision-making is a collective phenomenon. Collective behaviour emerges from the local interactions that give rise to a complex pattern at the group level. In our example, the recommendations or simple copying the choices of others make a crowded restaurant even more crowded. The rules of interaction between individuals are important to study. Such studies should be complemented by biological experiments. Recent studies of collective phenomena in animal groups help us to understand these rules and develop mathematical models of collective behaviour. The most important communication mechanism is positive feedback between group members, which we observe in our example. In this thesis, we use a generic experimentally validated model of positive feedback to study collective decision-making.
The first part of the thesis is based on the modelling of decision-making associated to the selection of feeding sites. This has been extensively studied for ants and slime moulds. The main contribution of our research is to demonstrate how such aspects as "irrationality", speed and quality of decisions can be modelled using differential equations. We study bifurcation phenomena and describe collective patterns above critical values of a bifurcation points in mathematical and biological terms. In the second part, we demonstrate how the primitive unicellular slime mould Physarum Polycephalum provides an easy test-bed for theoretical assumptions and model predictions about decision-making. We study its searching strategies and model decision-making associated to the selection of food options. We also consider the aggregation model to investigate the fractal structure of Physarum Polycephalum plasmodia.