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Using agents for developing intrusion detection systems can provide several advantages, including configurability, adaptability, scalability, and robustness. Almost all works in agent-based intrusion detection have considered agents as elements that perform specific tasks in the intrusion detection process. In this paper, we propose a novel way of using agents to solve one of the most pressing problems in intrusion detection: the definition of an accurate model of network normality. We consider agents as associated to partial models of network normality that harmonize their conflicts via cooperative negotiation. Experimental results show that the proposed approach is promising.