Abstract
Fuzzy cellular models (FCM) are a combination of cellular automata (CA) and fuzzy logic (FL). FCM are used to simulate complex dynamics ecological systems that involve space and time. The goal of this paper was to define a population growth model as a transition function that determines the state of each cell. The transition function involves FL to model variability of mortality, reproduction and emigration rates in each cell, based on the uncertainty that exists in the variation of the environment on the cellular space. The validation of the model was made within a comparative frame with others two population models, in one of them variability in the mortality and reproduction rates is not considered, and the other one is the Verhulst's model, wherein these rates are constants and there is no emigration. The results demonstrate that a FCM represents the population growth better than the others two models.