具有抑制性和兴奋性耦合的网络中（双）多方性的出现
Emergence of (bi)multi-partiteness in networks having inhibitory and excitatory couplings
摘要：
（Bi）多部分相互作用模式通常在具有抑制性和兴奋性耦合的现实世界系统中观察到。我们假设这些结构的相互作用模式是稳定的，在进化过程中自然产生的。我们证明了一个随机结构的（双）多部结构的进化施加稳定性标准，通过最大的特征值最小化的遗传算法设计的相互作用单元具有抑制性和兴奋性耦合。演化的交互模式对初始网络架构的变化以及交互权重的波动具有鲁棒性。
英文摘要：
(Bi)multi-partite interaction patterns are commonly observed in real world systems which have inhibitory and excitatory couplings. We hypothesize these structural interaction pattern to be stable and naturally arising in the course of evolution. We demonstrate that a random structure evolves to the (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 fluctuations in the interaction weights.
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