Patterns of cooperation: fairness and coordination in networks of interacting agents

We study the self-assembly of a complex network of collaborations among self-interested agents. The agents can maintain different levels of cooperation with different partners. Further, they continuously, selectively, and independently adapt the amount of resources allocated to each of their collaborations in order to maximize the obtained payoff. We show analytically that the system approaches a state in which the agents make identical investments, and links produce identical benefits. Despite this high degree of social coordination some agents manage to secure privileged topological positions in the network enabling them to extract high payoffs. Our analytical investigations provide a rationale for the emergence of unidirectional non-reciprocal collaborations and different responses to the withdrawal of a partner from an interaction that have been reported in the psychological literature.Comment: 20 pages, 8 figure

A dynamical mechanism for the evolution and breakdown of cooperation in the snowdrift game in adaptive networks

We present a novel dynamical mechanism promoting cooperation in the snowdrift game on an adaptive network. In infinite systems, asymptotic full cooperation can be achieved, while sudden breakdowns of highly cooperative states are observed in finite systems