Modeling diffusion of innovations with probabilistic cellular automata
arXiv:adap-org/9705004 · doi:10.1007/978-94-015-9153-9_9
Abstract
We present a family of one-dimensional cellular automata modeling the diffusion of an innovation in a population. Starting from simple deterministic rules, we construct models parameterized by the interaction range and exhibiting a second-order phase transition. We show that the number of individuals who eventually keep adopting the innovation strongly depends on connectivity between individuals.
17 pages, 5 figures