  This study proposed a model to give a full-scale simulation for the dynamics
of the collaborations in the dblp dataset. It is a distributed model with the
capability of simulating large hypergraphs, namely systems with heterogeneously
multinary relationship. Its assembly mechanism of hyperedges is driven by
Lotka's law and a cooperative game that maximizes benefit-cost ratio for
collaborations. The model is built on a circle to express the game, expressing
the cost by the distance between nodes. The benefit of coauthoring with a
productive researcher or one with many coauthors is expressed by the cumulative
degree or hyperdegree of nodes. The model successfully captures the
multimodality of collaboration patterns emerged in the dblp dataset, and
reproduces the evolutionary trends of collaboration pattern, degree,
hyperdegree, clustering, and giant component over thirty years remarkably well.
This model has the potential to be extended to understand the complexity of
self-organized systems that evolve mainly driven by specific cooperative games,
and would be capable of predicting the behavior patterns of system nodes.
