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Unsupervised Collective as a Simulation Tool for Social Networks

We present a model of a group of identical agents that may be used to simulate knowledge diffusion in social networks. At this time the model is still in development phase, but it includes notions derived from sociological theories as well as mathematical apparatus from the collective intelligence area. In this paper the model is extended by dynamic memory of agents, allowing them to forget knowledge. The model is tested in simulations based on criteria that were derived from sociological research describing functional real-world groups. We discuss in detail the combination of model elements giving most realistic results and present description of additional details that need to be included in the model to make it more similar to real-world groups.