BioND — Dynamics of Biological Networks

Evolution and failure of cooperation

When thinking of biological interactions, phrases like "survival of the fittest" and "eat and being eaten" come to mind. However, for biology, cooperation is perhaps even more important than competition and predation. Cooperation is found in all major families and extends down to unicellular organism. On a deeper level life itself is a cooperative phenomenon as genes cooperate to form proteins and cells cooperate to form tissues and organisms.

Cooperation is typically costly to the cooperator, requiring an investment of energy, resources, or time, which can be translated into a reduction of the individual’s reproductive potential. It is therefore intriguing to ask how cooperation has evolved through a process of natural selection that occurs on the level of the individual. The high level of cooperation observed in nature can only be explained if mechanisms exist by which helping others also conveys a benefit to the cooperator, or at least the genes of the cooperator. Uncovering these mechanism is a central challenge of evolutionary game theory. While several breakthroughs have recently been made the evolution of cooperation continues to be a highly active field of research.

We use a variety of different modeling approaches to understand how cooperation can emerge and why it sometimes fails. In particular, we proposed a new modeling approach for cooperation that, in contrast to earlier models, allows agents to maintain different levels of cooperation with different self-chosen partners (Do et al. 2010). We showed that this model, while being relatively simple and analytically tractable, reproduces observations from both psychology and population biology. For instance it exhibits the formation of complex networks of cooperation in which the agents coordinate their investments, the emergence of leaders which hold distinguished positions in the network, and the existence of different responses to the withdrawal of a partner from a collaboration.

Our present results constitute an important prove of principle: They show that the proposed methodology allows an efficient analysis of dynamic networks of dynamic social interactions, which will in the future enable us to study models of cooperation populations that provide much more ecological realism than previous game-theoretical models.

An important goal is therefore to apply our present model to realistically describe cooperation in populations of higher animals (e.g. primates, dolphins, zebras) for which empirical data is available.

Key Publications

Emergent bipartiteness in a society of knights and knaves
Charo del Genio and Thilo Gross
New Journal of Physics 13, 103038, 2011.
(abstract) (link to publisher) (arXiv) (download preprint)

Patterns of cooperation: fairness and coordination in self-organized networks of interacting agents
Anne-Ly Do, Lars Rudolf, and Thilo Gross
New Journal of Physics 12, 063023-19, 2010.
(abstract) (link to publisher) (arXiv) (download preprint) (media coverage)

A homoclinic route to full cooperation in adaptive networks and its failure
Gerd Zschaler, Arne Traulsen, and Thilo Gross
New Journal of Physics 12, 093015-12, 2010.
(abstract) (link to publisher) (arXiv) (download preprint)

Additional Publications

Coordination, differentiation, and fairness in a population of cooperating agents
Anne-Ly Do, Lars Rudolf, and Thilo Gross
Games 3, 30-40, 2012.
(abstract) (link to publisher) (arXiv) (download preprint)

Weighted trade network in a model of preferential bipartite transactions
Abhijit Chakraborty and Subhrangshu S. Manna
Physical Review E 81, 016111-8, 2010.
(abstract) (link to publisher) (arXiv) (download preprint)

Branching process in a stochastic extremal model
Subhrangshu S. Manna
Physical Review E 80, 021132-5, 2009.
(abstract) (link to publisher) (download preprint)

Adaptive coevolutionary networks: a review
Thilo Gross and Bernd Blasius
Journal of the Royal Society Interface 5(20), 259-271, 2008.
(abstract) (link to publisher) (arXiv) (download preprint)

Generalized models as an universal approach to the analysis of nonlinear dynamical systems
Thilo Gross and Ulrike Feudel
Physical Review E 73, 016205-14, 2006.
(abstract) (link to publisher) (arXiv) (download preprint)

Media Coverage

Sabiene Sütterlin, Science Blogs, 2010-08-26
Seit ich mit der Netzwerk-Gruppe zu tun habe, sehe ich überall Netzwerke. Die Leser dieses Blogs sind teilweise untereinander vernetzt, zum Beispiel. Und die Nervenzellen in unseren Gehirnen knüpfen stets neue Verbindungen

Jan Lublinski, German Public Radio (Deutschlandfunk), 2009-09-10
Netzwerke sind allgegenwärtig, sowohl in der Natur als auch in der menschlichen Gesellschaft. Aber es gibt nur sehr wenige mathematische Methoden, mit denen man Veränderungen in Netzwerken beschreiben kann. Eine Dresdner Wissenschaftlerin geht hier neue Wege
(more) (mp3 audio)