Zhang Si-ying

Consensus of Multi-Agent Systems with Prestissimo Scale-Free Networks

In this paper, the relations of the network topology and the moving consensus of multi-agent systems are studied. A consensus-prestissimo scale-free network model with the static preferential-consensus attachment is presented on the rewired link of the regular network. The effects of the static preferential-consensus BA network on the algebraic connectivity of the topology graph are compared with the regular network. The robustness gain to delay is analyzed for variable network topology with the same scale. The time to reach the consensus is studied for the dynamic network with and without communication delays. By applying the computer simulations, it is validated that the speed of the convergence of multi-agent systems can be greatly improved in the preferential-consensus BA network model with different configuration.

Opinion formation with time-varying bounded confidence related to the node degree

People like to communicate with others who have similar opinions in daily life. “Open” individuals are willing to accept peers’ opinions, whereas “conservative” individuals are more closed to others’ opinions. Based on this reality, an opinion dynamic model is proposed with a time-varying trust threshold related to the node degree, which refers to the number of individuals that can be communicated directly. Similar opinions within the trust thresholds at the beginning will eventually form a consensus opinion. Individuals who have common neighbors converge to consensus faster than ones who have no common neighbors. The network size impacts the convergent speed of the opinion cluster and the trust threshold cluster. Individuals in small groups are more stressed than in large ones when they try to insist their opinions. A group with half of the individuals categorized as doubting and the other half categorized as trusting exhibits consistent confidence but experiences difficulty in reaching a consensus: “harmony but difference” may be a criterion for unifying a group.

Weighted evolving network with geographical constraints

Complex networks have established themselves as being particularly suitable and flexible for representing and modeling several complex natural and human-made systems. Inspired by studies on airline and shipping networks, we propose a transport network model that includes geographical attributes along with topological and weight properties. In this model we introduce the theory of cost in micro-economics, regard distance between vertices as a function of cost. In general, a long-range connection cost higher and happen to appear rarely based on this, in our model the topological growth and weight dynamics are both determined by geographical distance cost and capacity of dealing with traffic load in a given vertex. Then we analyze some attributes of this model, the results suggest that the interplay between weight dynamics and spatial constraints is a key ingredient in order to understand the underlying driving factor of real-world weighted networks.