  EVOC is a computer model of the EVOlution of Culture. It consists of neural
network based agents that invent ideas for actions, and imitate neighbors'
actions. EVOC replicates using a different fitness function the results
obtained with an earlier model (MAV), including (1) an increase in mean fitness
of actions, and (2) an increase and then decrease in the diversity of actions.
Diversity of actions is positively correlated with number of needs, population
size and density, and with the erosion of borders between populations. Slowly
eroding borders maximize diversity, fostering specialization followed by
sharing of fit actions. Square (as opposed to toroidal) worlds also exhibit
higher diversity. Introducing a leader that broadcasts its actions throughout
the population increases the fitness of actions but reduces diversity; these
effects diminish the more leaders there are. Low density populations have less
fit ideas but broadcasting diminishes this effect.
