On convergence of dynamic cluster formation in multi-agent networks

Mikhail Prokopenko*, Piraveenan Mahendra Rajah, Peter Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

8 Citations (Scopus)

Abstract

Efficient hierarchical architectures for reconfigurable and adaptive multi-agent networks require dynamic cluster formation among the set of nodes (agents). In the absence of centralised controllers, this process can be described as self-organisation of dynamic hierarchies, with multiple cluster-heads emerging as a result of inter-agent communications. Decentralised clustering algorithms deployed in multi-agent networks are hard to evaluate precisely for the reason of the diminished predictability brought about by self-organisation. In particular, it is hard to predict when the cluster formation will converge to a stable configuration. This paper proposes and experimentally evaluates a predictor for the convergence time of cluster formation, based on a regularity of the inter-agent communication space as the underlying parameter. The results indicate that the generalised "correlation entropy" K2. (a lower bound of Kolmogorov-Sinai entropy) of the volume of the inter-agent communications can be correlated with the time of cluster formation, and can be used as its predictor.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMathieu S. Capcarrere
Place of PublicationBerlin; New York
PublisherSpringer, Springer Nature
Pages884-894
Number of pages11
Volume3630 LNAI
ISBN (Print)3540288481, 9783540288480
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event8th European Conference on Advances in Artificial Life, ECAL 2005 - Canterbury, United Kingdom
Duration: 5 Sep 20059 Sep 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3630 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other8th European Conference on Advances in Artificial Life, ECAL 2005
CountryUnited Kingdom
CityCanterbury
Period5/09/059/09/05

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