Purpose -The purpose of this paper is to analyse the role of computational intelligence techniques in the process of communities' formation. Design/methodology/approach -The paper develops a high performance genetic algorithm for community formation based on collective intelligence capacity. An experimental study is presented to illustrate the algorithm. Findings -Collective intelligence does not represent the sum of individual intelligences, it is the ability of the community to complete more tasks than single individuals. The paper reveals the need for mechanisms that allow a large group of professionals to make decisions better than single individuals. Practical implications -The genetic algorithm proposed in the paper may be used to obtain the optimal structure of a community, in terms of number of members and their role in the community. Originality/value -The key concept is a new fitness index, an intelligence index, which is the optimal combination between intelligence and cooperation, and allows not only community formation, but also intelligence to be the driving principle in the community formation process.
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