The aim of this paper is to present an agent-based model for network flows self-management implemented in NetLogo 6. Currently, network self-management is supported by artificial intelligence techniques for decision-making tasks. The incorporation of intelligent agents and a negotiation algorithm enable the performance of automatic actions to maintain and improve the flow management in the network. This research paper describes the analysis of a network using a complex systems approach and presents a negotiation algorithm based on preferences and hidden authorities to coordinate the delivery of the flows when a congestion situation emerge.
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