TY - JOUR A2 - Amancio, Diego R. AU - Villani, Marco AU - Sani, Laura AU - Pecori, Riccardo AU - Amoretti, Michele AU - Roli, Andrea AU - Mordonini, Monica AU - Serra, Roberto AU - Cagnoni, Stefano PY - 2018 DA - 2018/11/11 TI - An Iterative Information-Theoretic Approach to the Detection of Structures in Complex Systems SP - 3687839 VL - 2018 AB - Systems that exhibit complex behaviours often contain inherent dynamical structures which evolve over time in a coordinated way. In this paper, we present a methodology based on the Relevance Index method aimed at revealing the dynamical structures hidden in complex systems. The method iterates two basic steps: detection of relevant variable sets based on the computation of the Relevance Index, and application of a sieving algorithm, which refines the results. This approach is able to highlight the organization of a complex system into sets of variables, which interact with one another at different hierarchical levels, detected, in turn, in the different iterations of the sieve. The method can be applied directly to systems composed of a small number of variables, whereas it requires the help of a custom metaheuristic in case of systems with larger dimensions. We have evaluated the potential of the method by applying it to three case studies: synthetic data generated by a nonlinear stochastic dynamical system, a small-sized and well-known system modelling a catalytic reaction, and a larger one, which describes the interactions within a social community, that requires the use of the metaheuristic. The experiments we made to validate the method produced interesting results, effectively uncovering hidden details of the systems to which it was applied. SN - 1076-2787 UR - https://doi.org/10.1155/2018/3687839 DO - 10.1155/2018/3687839 JF - Complexity PB - Hindawi KW - ER -