Cellular Automata Models for Diffusion of Innovations

dc.creatorFuks, Henryk
dc.creatorBoccara, Nino
dc.date1997-04-08
dc.date.accessioned2026-07-07T09:05:36Z
dc.date.available2026-07-07T09:05:36Z
dc.descriptionWe propose a probabilistic cellular automata model for the spread of innovations, rumors, news, etc. in a social system. The local rule used in the model is outertotalistic, and the range of interaction can vary. When the range R of the rule increases, the takeover time for innovation increases and converges toward its mean-field value, which is almost inversely proportional to R when R is large. Exact solutions for R=1 and $R=\infty$ (mean-field) are presented, as well as simulation results for other values of R. The average local density is found to converge to a certain stationary value, which allows us to obtain a semi-phenomenological solution valid in the vicinity of the fixed point n=1 (for large t).
dc.description13 pages, 6 figures
dc.identifierhttps://arxiv.org/abs/adap-org/9704002
dc.identifierhttp://arxiv.org/abs/adap-org/9704002
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/149730
dc.subjectAdaptation and Self-Organizing Systems
dc.titleCellular Automata Models for Diffusion of Innovations
dc.typetext

Files

Collections