… performance 55 and the size of social networks and this may have been the case for our
ancestors, helping them better survive hostile environments as they migrated and populated the …

… the topology of resulting social network and dynamics of majority opinion acceptance. … a
model of consensus formation that takes into account not only factors leading to convergence of …

… the consensus through a collapse (see Fig. 2(a)–(c)), in contrast to the soft convergence of
the two opinion clusters into the consensus for 0.25 < p < 0.9 (see Fig. 2, (d) through (g)). Fig. …

… consensus level is lower than the threshold, or the cluster consensus level is lower than the
group consensus … In this context, the clusters should be continuously converging toward the …

… of consensus has been less explored compared to the abundant study of convergent or
non-convergent … We argue that consensus is of crucial importance to multi-agent learning—it …

… , consensus algorithms of the form (1.1) are used as stylized models of opinion formation and
updating in social networks… -theoretic structure of social networks and the detailed features …

… Therefore, the design of consensus reaching mechanism should consider both the
convergence and feasibility. In this paper, we propose a novel feedback strategy called parallel …

… trait through different social network structures we show that the type of social … consensus
with respect to its members’ arbitrary trait. We define consensus in this case as a convergence …

… insight on social groups, we examine a stochastic leader–follower consensus problem
where … In order to quantify the rate of convergence to consensus, we introduce the asymptotic …

… of paracontracting operators, we derive general convergence criteria that are relevant for a
wide … for consensus for various social networks by simulating several network topologies and …