群智体系网络结构的自治调节:从生物调控网络结构谈起

Autonomous Structural Adjustment of Crowd Intelligence Network:Begin from Structure of Biological Regulatory Network

群体智能作为人工智能2.0时代最突出的研究方向之一,受到了工业界和学术界研究者们的广泛关注。传统的人工智能模型倾向于使用全连通网络结构,认为全连通网络结构的人工智能模型具有更高的准确率。然而,在面对存在强干扰的复杂对抗环境时,智能决策体系需要面对由通信干扰甚至针对性攻击所造成的系统结构扰动。在不失准确性的前提下,为了能够更快、更稳定地进行实时响应,需要智能系统的结构具有实时自治响应调整机制。此类自治响应调整机制在自然界中的调控网络中很常见。文中通过引入DReSS表征族来定量分析随机网络与真实网络中结构扰动对于系统演化的影响,对比了不同网络结构对于结构扰动的抗干扰能力,并提出了一套群智体系网络结构的自治调节构想。

As one of the most important research directions in the artificial intelligence 2.0 era,crowd intelligence has received extensive attention from researchers in the industry and academia.Traditional artificial intelligence models tend to use the fully connected network structure to achieve higher accuracy.However,in a complex confrontation environment with strong interfe-rence,the intelligent decision-making system needs to face system structural perturbations caused by communication interference or even targeted attack.Without losing too much accuracy,in order to achieve the demand for faster and more stable real-time response,it is necessary for intelligent system to have a real-time autonomous response structural adjustment mechanism.Such autonomous corresponding adjustment mechanisms are common in regulatory networks for biological systems.By introducing DReSS index family,this research quantitatively analyzes the impact of structural perturbations on state spaces in random and real networks.The anti-interference feature of different network structures against structural perturbations is compared.An autonomous adjustment concepts for the network structure of the crowd intelligence systems is proposed in this research.