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It is significant for a MCS (mine countermeasure system) to recognize the model of a water mine exactly in order to take right destroying measures. In this paper, the ABNET proposed by L.N. de Castro is simplified and employed in a multi-agent-based MCS for fusing the feature data and recognizing the model of water mines. The simplified ABNET (sABNET) is a two-layer Boolean network which number of outputs is adaptable according to the task and which recognition precision can be controlled by the immune affinity threshold. Compared with Castro's work, the sABNET converges more quickly.