Emergence of Collective Cooperation and Networks from Selfish-Trust and Selfish-Connections

AbstractEmergence of collective cooperation in an inherently selfish society is a paradox that has preoccupied biologists, sociologists, and cognitive scientists alike for centuries. We propose a computational model and demonstrate through simulations how collective cooperation can emerge from selfish interests: the goal of improving each individual’s own rewards. We also demonstrate how the same selfish interests lead to the dynamic emergence of a network of interconnected agents. Our model includes two simple mechanisms: Selfish-Trust (ST) and Selfish-Connection (SC). ST involves the possibility of relying on others in a society of agents when it is beneficial to the individual, and SC involves the possibility of connecting to other agents when those agents help improve the individual’s own benefit. Our simulation results suggest that collective cooperation can emerge from ST and a complex dynamic network can emerge from ST and SC. The simulated data demonstrate an important property of many living organisms: patterns of temporal complexity, which are essential to transfer information among agents of any society of living beings.


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