Christian Hilbe

Christian will start his research group at the MPI in summer.
Please contact Christian for further information on the project:

Evolution of cooperation and reciprocity in changing environments

Humans have a remarkable tendency to cooperate with each other even in situations in which cooperation is not in their immediate self-interest. One mechanism that allows for the comparably high cooperation rates in humans is reciprocity. Cooperative behaviours are often remembered, and subsequently rewarded, either in form of direct compensations (direct reciprocity) or an increased reputation (indirect reciprocity).

Traditionally, research on reciprocity has often assumed that individuals interact in a constant environment. That is, during their lives, individuals are assumed to encounter the same kinds of social dilemmas over and over again. If one individual cooperates today, other individuals always have a chance to reciprocate in kind tomorrow. This assumption turns out to be crucial for the evolution of reciprocity, because individuals can reliably forecast how costly future cooperation will be. In contrast, with this project we want to explore how individuals cooperate in situations in which their environment can change over time, and where the cooperation costs may fluctuate. We would like to know which strategies individuals employ to cope with this increased complexity, and under which conditions reciprocity can still evolve.

There are two alternative (but not mutually exclusive) ways how to study these questions. The first approach is based on formal modelling. To this end, the above questions are translated into a theoretical framework, and then explored mathematically or with simulations. The second approach is based on behavioural laboratory experiments with humans. Here, we translate the above questions into simple game situations, we recruit student subjects to interact in these games, and we statistically analyse their behaviours.

Candidates should have a genuine interest in human behaviour and cooperation. For candidates who wish to pursue the first approach, a solid mathematical background and some simulation skills are certainly useful. For candidates who are interested in the second approach, some programming skills and a basic understanding of statistics is required.


Key paper:

Hilbe, Simsa, Chatterjee, Nowak (Nature 2018) “Evolution of cooperation in stochastic games”

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