Models of Dynamical Modelling Under Uncertainty

The objective of this work is to modelize the evolution of a Model-System to be adapted to a Random System. This evolution is described by means of the change of a probabilistic function, through deterministic rules and in function of the random responses of the modelized System. This probabilistic function can describe the relative weight of distinct submodels (deterministic or random Systems, with constant or variable stimulus), or the stimulus-response relation in the Model-System (Adaptative Random System). We conclude that the Adaptative Random Model permits a more precise, simple and economical modelling.

Simulation of the anomalous social behaviours with a learning model

In this paper our objective is to understand the process of emergence in the study of social behaviours evolution with a learning model. When the system is too complex to study it is important to recreate an artificial universe in which experiments’ simulation can help to understand the mechanisms of human social behaviours. In Previous work we determined the conditions that favour the perpetuity of the Capitalist Globalization, the possibility of its overcoming with a Free Scientific Society and the possibility of the Ecological Hecatomb. In this paper we have theoretically explained the emergence of the anomalous behaviours and developed statistical studies of the conditions that favour t…

Modelling “Occident/Orient” duality and migration process with mobile agents