BIRCH: an efficient data clustering method for very large databases
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This research paper gives an overview of several clustering methods and presents their application in formation and reconfiguration of coalitions of agents cooperating in dynamically evolving environment. Our experimental generator of coalitional structures takes into account both the stability of resulting coalitions and efficiency of computations. It focuses on providing average-case optimal solution and generates coherent stable groups with respect to agents beliefs, intentions, capabilities as well as the current environmental state. Clustering based approach leads to a robust adaptation of existing structure in response to changing environmental conditions, even in case of complex, high-dimensional models. Among numerous future research challenges listed in the last section, an adaptive approach based on evolutionary models is outlined.