Private list sharing leads to cooperation and central hubs emergence in ABM

We introduce an agent based model framework to investigate how an alternative to classic image score and gossip can support the emergence of cooperation in a repeated prisoner dilemma game with agents employing mixed strategies. We debate the universality of image scores, arguing that they cannot be considered an objective property of the agents observed but rather a subjective property of each observer. From this assumption, we develop a private list mechanism for opponent selection and gossip sharing among the population of the simulation. The results show that the private list mechanism is able to foster the emergence of cooperation, and that for various levels of list usage different levels of cooperation correspond in the system. Finally, we observe interesting topological properties emerging, with networks characterised by one 'super-hub' connected to every other node, suggesting the emergence of centralized entities to support cooperation.