Social Networks and Norms Evolution

There has been a lot of interest around social norms evolution which can explain the dynamics on how social norms evolve from ground-up. The literature has shown that self-interested agents with very little information about other agents have shown cooperative behaviour while interacting with other agents. The choices people make are interdependent and dynamic in the sense that people’s aspiration levels vary over time and are dependent upon the network they are a part of at any given point in time. The choices made are also usually based upon heuristics and some rules of thumb. We have shown this computationally how norms evolve from the ground-up wherein agents interact with other agents in their network and decide what action to take without engaging in any complex calculations. Norms once established can be displaced and replaced by new norms depending upon agents’ incentives and network structures. We have provided the computational framework in the form of two open-source python libraries which can be leveraged to evaluate how norms evolve among agents who don’t know about other agents’ identity and take actions dynamically based upon user defined custom parameters on networks, neighbourhood size, population size, number of time periods etc.