2013/10/31 by Liane Gabora · 2 citations
Computer Science · #cs.MA #cs.NE
published as Gabora, L. (2008). EVOC: A computer model of cultural evolution. In V. Sloutsky, B. Love & K. McRae (Eds.), 30th Annual Meeting of the Cognitive Science Society. Washington DC, July 23-26, North Salt Lake, UT: Sheridan Publishing · 6 pages. arXiv admin note: substantial text overlap with arXiv:1005.1516, arXiv:0911.2390, arXiv:0811.2551; replaced version corrects error in reference at top of first page
arxiv created 2014/09/03 · arxiv updated 2014/09/04
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.