| Systems Biology is an interdisciplinary field that pursues data-driven,
model-based studies of biological organisms and functions. The use of
quantitative models is intended to be tightly coupled with biological
knowledge. Within this project, we pursue the development of
quantitative models for the so-called predator-prey problems to study
and understand competition and cooperation among organisms interacting
within a resource-constrained environment.
The theory of evolutionary games provides the basis for
understanding the interaction and the dynamics between populations of
such organisms. The solution of these games over sets of possible
strategies is related to specific optimality conditions for the
populations under study. An important question is whether such
strategies are evolutionary stable, i.e. unbeatable under given initial
conditions.
We intend to develop game-theoretical models for predator-prey systems,
describing the intra-seasonal (continuous) and inter-seasonal (discrete)
dynamics. Collaboration with colleagues in biology is a key element in the derivation of such models. Individual models together with pre-specified metrics of optimality of the interacting
species will form hybrid games of the Nash or Stackelberg type. Firstly,
by solving such games we will find optimal strategies for the involved
populations. Secondly, we will investigate for which parameter domains
these strategies are evolutionary stable.
Another goal of this project is construction of new, ad-hoc optimality
conditions over the considered game-theoretical problems. The use of
new metrics for optimality will allow to establish a framework to
understand survival properties, competitive strategies, as well as
cooperative behaviors among interacting populations of organisms.
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