We introduce time variation in the flip-rates of the Voter Model. This type
of generalisation is relevant to models of ageing in language change, allowing
the representation of changes in speakers' learning rates over their lifetime
and may be applied to any other similar model in which interaction rates at the
microscopic level change with time. The mean time taken to reach consensus
varies in a nontrivial way with the rate of change of the flip-rates, varying
between bounds given by the mean consensus times for static homogeneous (the
original Voter Model) and static heterogeneous flip-rates. By considering the
mean time between interactions for each agent, we derive excellent estimates of
the mean consensus times and exit probabilities for any time scale of flip-rate
variation. The scaling of consensus times with population size on complex
networks is correctly predicted, and is as would be expected for the ordinary
voter model. Heterogeneity in the initial distribution of opinions has a strong
effect, considerably reducing the mean time to consensus, while increasing the
probability of survival of the opinion which initially occupies the most slowly
changing agents. The mean times to reach consensus for different states are
very different. An opinion originally held by the fastest changing agents has a
smaller chance to succeed, and takes much longer to do so than an evenly
distributed opinion.Comment: 16 pages, 6 figure