Abstract
(Bi)multi-partite interaction patterns are observed frequently in real-world systems which have inhibitory and excitatory couplings. We hypothesize these structural interaction patterns to be stable and naturally arising in the course of evolution. We demonstrate that a random structure evolves to a (bi)multi-partite structure by imposing stability criterion through minimization of the largest eigenvalue in the genetic algorithm devised on the interacting units having inhibitory and excitatory couplings. The evolved interaction patterns are robust against changes in the initial network architecture as well as against fluctuations in the interaction weights.
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