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Self-adaptation in Collective Self-aware Computing Systems

  • Jeffrey O. Kephart
  • , Ada Diaconescu
  • , Holger Giese
  • , Anders Robertsson
  • , Tarek Abdelzaher
  • , Peter Lewis
  • , Antonio Filieri
  • , Lukas Esterle
  • , Sylvain Frey
  • IBM Watson Research Center
  • Université Paris-Saclay
  • Hasso Plattner Institute
  • Department of Automatic Control
  • University of Illinois at Urbana-Champaign
  • Aston University
  • Imperial College London
  • Vienna University of Technology
  • Lancaster University

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collectionChapitreRevue par des pairs

Résumé

The goals of this chapter are to identify the challenges involved in selfadaptation (including learning and knowledge sharing) of multiple self-aware systems (or system collectives). We shall discuss the techniques available for dealing with the challenges identified (e.g., algorithms for conflict resolution, collective learning, and negotiation protocols), and which are appropriate given assumptions regarding the collective system architecture.We refer to notions of knowledge, learning, and adaptation; various self-awareness levels; and reference scenarios introduced in Chap. 4.

langue originaleAnglais
titreSelf-Aware Computing Systems
EditeurSpringer International Publishing
Pages401-435
Nombre de pages35
ISBN (Electronique)9783319474748
ISBN (imprimé)9783319474724
Les DOIs
étatPublié - 21 févr. 2017
Modification externeOui

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