Abstract
The presence of costly cooperation between otherwise selfish actors is not trivial. A prominent mechanism that promotes cooperation is spatial population structure. However, recent experiments with human subjects report substantially lower level of cooperation then predicted by theoretical models. We analyze the data of such an experiment in which a total of 400 players play a Prisoner's Dilemma on a square lattice in two treatments, either interacting via a fixed square lattice (15 independent groups) or with a population structure changing after each interaction (10 independent groups). We analyze the statistics of individual decisions and infer in which way they can be matched with the typical models of evolutionary game theorists. We find no difference in the strategy updating between the two treatments. However, the strategy updates are distinct from the most popular models which lead to the promotion of cooperation as shown by computer simulations of the strategy updating. This suggests that the promotion of cooperation by population structure is not as straightforward in humans as often envisioned in theoretical models.
Highlights
Why would a self-interested individual pay towards the welfare of someone else? The evolution of cooperation is a fascinating problem originating in evolutionary biology [1,2,3] which has extended to several other disciplines subsequently [4,5,6,7]
While mutual cooperation leads to a higher payoff than mutual defection, it is worthwhile to defect against a cooperator (TwR) and to defect against a defector (PwS), In addition to this payoff ranking, the condition 2RwTzS should be added in repeated games
We have found no significant differences between the two treatments, neither in macroscopic properties such as the level of cooperation, nor in the way that players update their strategies
Summary
Why would a self-interested individual pay towards the welfare of someone else? The evolution of cooperation is a fascinating problem originating in evolutionary biology [1,2,3] which has extended to several other disciplines subsequently [4,5,6,7]. Regular lattices lead to interesting effects and dependences on details of the underlying evolutionary model [10,11,12,13,14,15,16,17,18,19,20]. The exploration of non-regular population structures, such as scale-free networks, suggest an intricate dependence on details of the population structure and update mechanisms [18,21,22,23,24,25,26]. Even more complex effects arise when the underlying population structure is dynamic [27,28,29,30,31,32]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
