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Information retrieval techniques have to face both the growing amount of data to be processed and the "natural"' distribution of these data over the network. Hence, we introduce in this paper a new architecture for image retrieval in distributed image databases, based on multi-agent, systems. Our system, inspired by "ant-agents", uses labels provided by the user for learning both the searched category of images and die path to the most relevant databases. We then show how effective can be our architecture on a generalist image database network.