Agreement over random networks

By Yuko Hatano, Mehran Mesbahi. 2004

671 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Molecular Biology

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In Computer Networks and Communications

In Molecular Biology

Citations in the corpus

An Overview of Recent Progress in the Study of Distributed Multi-Agent Coordination (2012, background): “Consensus over a stochastic network topology was perhaps first studied in [32], where some sufficient conditions on the network topology were given to guarantee consensus with probability one for systems with single-integrator kinematics equation (1), where the rate of convergence was also studied.”
Finite-Time Consensus Problems for Networks of Dynamic Agents (2007, background): “In th e past few years, consensus problems of multi-agent systems have been developing fast and many rese arch topics have been addressed, such as agreement over random networks [6], [7], asynchrono us information consensus [8], dynamic consensus [9], networks with nonlinear consensus p rotocols [10”
Asynchronous consensus of continuous-time multi-agent systems with intermittent measurements (2010, background): “…Olfati-Saber and Murray 2004, Ren and Beard 2005), finite-time consensus (Corte´s 2006; Xiao, Wang, and Jia 2008), consensus over random networks (Hatano and Mesbahi 2005, Porfiri and Stilwell 2007), optimal consensus (Semsar-Kazerooni and Khorasani 2008), asynchronous consensus (Cao, Morse,…”
Consensus of multi-agent systems with intrinsic nonlinear dynamics and sampled-data information (2011, background): “In fact, active research on consensus problems is still ongoing today, such as consensus seeking under stochastic disturbances [9], [10], consensus over random networks [11], [12], consensus with diverse time-delays [13], and high-order consensus [14]–[16].”
Consensus and Cooperation in Networked Multi-Agent Systems (2007, methodology): “Proof: See the proof of Proposition 2 in [ 14 ].”
Distributed Consensus Algorithms in Sensor Networks With Imperfect Communication: Link Failures and Channel Noise (2007, background): “considered separately. Random link failures, but noiseless consensus, is in [11], [ 12 ], [13], [14], [15],”
Coordination and Consensus of Networked Agents with Noisy Measurements: Stochastic Algorithms and Asymptotic Behavior (2009, methodology): “problems, and [21] used an approach of stochastic stability.”
Information consensus in multivehicle cooperative control (2007, background): “Information consensus is also studied from a stochastic point of view in [34]–[36], which consider a random network, in which the existence of an information channel between a pair of vehicles at each time is probabilistic and independent of other channels, resulting in a time-varying undirected com”
Broadcast Gossip Algorithms for Consensus (2009, background): “Then, almost surely converges to zero, i.e. (51) We have almost sure convergence if , for some since [7] (52) However, given , we have, as can be seen in the proof of Lemma 3, that (53) From the proof of Lemma 3 and Proposition 2, we know that (54) where .”
Controllability of Multi-Agent Systems from a Graph-Theoretic Perspective (2009, background): “An important class of problems that lies at this intersection pertains to the agreement or the consensus problem [4, 15, 28, 30, 39].”
Distributed Kalman filtering for sensor networks (2007, background): “Control-theoretic consensus algorithms have proven to be effective tools for performing network-wide distributed computation tasks such as computing aggregate quantities and functions over networks [13], [12], [17], [8], [23], [24], [21], [5].”
Convergence speed in distributed consensus over dynamically switching random networks (2009, background): “Hence, the observation for undirected random network that agents converge to the average of initial values Hatano and Mesbahi (2005) may not be applicable to directed random networks.”
Consensus Filters for Sensor Networks and Distributed Sensor Fusion (2005, background): “Consensus problems [18], [21] for networked dynamic systems have been extensively used by many researchers as part of the solution of more complex problems including collective control of motion of swarms/flocks of mobile agents [15], ultrafast consensus in small-world networks [16], [24], state-dep”