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Article: Improve consensus via decentralized predictive mechanisms

TitleImprove consensus via decentralized predictive mechanisms
Authors
Issue Date2009
PublisherInstitute of Physics Publishing Ltd.. The Journal's web site is located at http://iopscience.iop.org/0295-5075
Citation
Epl, 2009, v. 86 n. 4 How to Cite?
AbstractFor biogroups and groups of self-driven agents, making decisions often depends on interactions among group members. In this paper, we seek to understand the fundamental predictive mechanisms used by group members in order to perform such coordinated behaviors. In particular, we show that the future dynamics of each node in the network can be predicted solely using local information provided by its neighbors. Using this predicted future dynamics information, we propose a decentralized predictive consensus protocol, which yields drastic improvements in terms of both consensus speed and internal communication cost. In natural science, this study provides an evidence for the idea that some decentralized predictive mechanisms may exist in widely-spread biological swarms/flocks. From the industrial point of view, incorporation of a decentralized predictive mechanism allows for not only a significant increase in the speed of convergence towards consensus but also a reduction in the communication energy required to achieve a predefined consensus performance. © EPLA, 2009.
Persistent Identifierhttp://hdl.handle.net/10722/91394
ISSN
2015 Impact Factor: 1.963
2015 SCImago Journal Rankings: 0.565
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorZhang, HTen_HK
dc.contributor.authorChen, MZQen_HK
dc.contributor.authorZhou, Ten_HK
dc.date.accessioned2010-09-17T10:18:35Z-
dc.date.available2010-09-17T10:18:35Z-
dc.date.issued2009en_HK
dc.identifier.citationEpl, 2009, v. 86 n. 4en_HK
dc.identifier.issn0295-5075en_HK
dc.identifier.urihttp://hdl.handle.net/10722/91394-
dc.description.abstractFor biogroups and groups of self-driven agents, making decisions often depends on interactions among group members. In this paper, we seek to understand the fundamental predictive mechanisms used by group members in order to perform such coordinated behaviors. In particular, we show that the future dynamics of each node in the network can be predicted solely using local information provided by its neighbors. Using this predicted future dynamics information, we propose a decentralized predictive consensus protocol, which yields drastic improvements in terms of both consensus speed and internal communication cost. In natural science, this study provides an evidence for the idea that some decentralized predictive mechanisms may exist in widely-spread biological swarms/flocks. From the industrial point of view, incorporation of a decentralized predictive mechanism allows for not only a significant increase in the speed of convergence towards consensus but also a reduction in the communication energy required to achieve a predefined consensus performance. © EPLA, 2009.en_HK
dc.languageengen_HK
dc.publisherInstitute of Physics Publishing Ltd.. The Journal's web site is located at http://iopscience.iop.org/0295-5075 en_HK
dc.relation.ispartofEPLen_HK
dc.titleImprove consensus via decentralized predictive mechanismsen_HK
dc.typeArticleen_HK
dc.identifier.emailChen, MZQ:mzqchen@hku.hken_HK
dc.identifier.authorityChen, MZQ=rp01317en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1209/0295-5075/86/40011en_HK
dc.identifier.scopuseid_2-s2.0-79051469517en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79051469517&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume86en_HK
dc.identifier.issue4en_HK
dc.identifier.eissn1286-4854-
dc.identifier.isiWOS:000267292000011-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridZhang, HT=7409192616en_HK
dc.identifier.scopusauthoridChen, MZQ=35085827300en_HK
dc.identifier.scopusauthoridZhou, T=8575473800en_HK

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