A SYSTEM OF IAC NEURAL NETWORKS AS THE BASIS FOR SELF-ORGANIZATION INA SOCIOLOGICAL DYNAMICAL SYSTEM SIMULATION

This sociological simulation uses the ideas of semiotics and symbolic interactionism to demonstrate how an appropriately developed associati ve memory in the minds of individuals on the microlevel can sell-organ ize into macrolevel dissipative structures of societies such as racial cultural/economic classes, status symbols and fade. The associative m emory used is based on an extension of the IAC neural network (the Int eractive Activation and Competition network). Several IAC networks act together to form a society by virtue of their human like properties o f intuition and creativity. These properties give them the ability to create and understand signs which lead to the macrolevel structures of society. This system is implemented in hierarchical object oriented c ontainer classes which facilitate change in deep structure. Graphs of general trends and an historical account of a simulation run of this d ynamical system are presented.