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The set covering problem is a classical problem in computer science and complexity theory and it serves as a model for many real-world applications especially in the resource allocation area. In an environment where the demands that need to be covered change over time, special methods are needed that adapt to such changes. We have developed an incremental clustering algorithm in order to address the set covering problem. The algorithm continuously considers new items to be clustered. Whenever a new data item arrives it is encapsulated by an agent which will autonomously decide to be included in a certain cluster in the attempt to either maximize its cover or minimize the cost. We have introduced the soft agent model in order to encapsulate this behaviour. Initial tests suggest the potential of our approach.

Key words and phrases. Set covering problem, Incremental methods, Clustering, SCP datasets.