Coevolutionary update rule

Motivated by measurements on interevent time distributions of many human activities which show a heavy tail, we implemented an update rule coupled to the dynamics of the voter model to account for that characteristic. We couple the update rule to the dynamics by adding a memory to the agents that depends on the time they have been with the same opinion. As this time gets bigger, the agent is less probable to interact. We find the model to get different results than with the usual update rules. When the memory function we add is of the type \beta/\tau we find that the voter model makes its way to consensus even in the thermodynamic limit for high-dimensional networks.

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