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Asymptotic Consensus Without Self-Confidence

Thomas Nowak 1
1 DYOGENE - Dynamics of Geometric Networks
CNRS - Centre National de la Recherche Scientifique : UMR8548, Inria Paris-Rocquencourt, DI-ENS - Département d'informatique de l'École normale supérieure
Abstract : This paper studies asymptotic consensus in systems in which agents do not necessarily have self-confidence, i.e., may disregard their own value during execution of the update rule. We show that the prevalent hypothesis of self-confidence in many convergence results can be replaced by the existence of aperiodic cores. These are stable aperiodic subgraphs, which allow to virtually store information about an agent's value distributedly in the network. Our results are applicable to systems with message delays and memory loss.
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Submitted on : Friday, November 20, 2015 - 2:07:42 PM
Last modification on : Thursday, February 7, 2019 - 3:49:20 PM
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  • HAL Id : hal-01231503, version 1
  • ARXIV : 1301.3784



Thomas Nowak. Asymptotic Consensus Without Self-Confidence. 54th IEEE Conference on Decision and Control (CDC 2015), Dec 2015, Osaka, Japan. ⟨hal-01231503⟩



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