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Global consensus emergence in an unstructured semantic network

Published: 28 October 2008 Publication History

Abstract

A global semantic consensus can emerge from the self-organization of a population of distributed agents connected through some communication network and playing local collaborative games: in a recently proposed class of self-organizing Semantic Overlay Networks, inspired by the mechanics of the Ising spin model, the condition which grants the convergence to a global consensus (Representative Agent condition -- of everyone knowing about the state of everybody else) is approximated by an equivalent uniform sampling over the nodes. In this way a specific mapping from a set of symbols to a set of concepts can become a shared convention for a set of peers. However uniform sampling is a non-trivial issue in unstructured overlays: one of the main hurdles to an homogeneous information dissemination in a random network is represented by topological bottlenecks. Relevant examples of such obstructions are network-graph bridges: they have a straightforward characterization, in terms of network reliability, as links whose failure makes the graph disconnected, i.e. broken in two non mutually reachable components; regions of a graph connected by a bridge are called pseudo-components. Messages failing to cross a bridge can prevent the information from one pseudo-component to reach another pseudo-component: in such conditions different pseudo-components can settle on a consensus state on their own, which does not correspond to a global consensus. In this paper we describe a distributed algorithm that improves the mutual reachability of any pair of nodes in an unstructured network of arbitrary topology, so that each agent can potentially disseminate its own state more uniformly to all the components of the network: the algorithm is based on a self-establishing gradient mechanism and bears some similarity to algorithms such as the ant-colony algorithms.

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Cited By

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  • (2014)IoT-aided robotics applicationsComputer Communications10.1016/j.comcom.2014.07.01354:C(32-47)Online publication date: 1-Dec-2014
  • (2013)Learning by Gossip: A Principled Information Exchange Model in Social NetworksCognitive Computation10.1007/s12559-013-9211-65:3(327-339)Online publication date: 9-Mar-2013

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    cover image ACM Other conferences
    CSTST '08: Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
    October 2008
    733 pages
    ISBN:9781605580463
    DOI:10.1145/1456223
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    • The French Chapter of ACM Special Interest Group on Applied Computing
    • Ministère des Affaires Etrangères et Européennes
    • Région Ile de France
    • Communauté d'Agglomération de Cergy-Pontoise
    • Institute of Electrical and Electronics Engineers Systems, Man and Cybernetics Society
    • The European Society For Fuzzy And technology
    • Institute of Electrical and Electronics Engineers France Section
    • Laboratoire des Equipes Traitement des Images et du Signal
    • AFIHM: Ass. Francophone d'Interaction Homme-Machine
    • The International Fuzzy System Association
    • Laboratoire Innovation Développement
    • University of Cergy-Pontoise
    • The World Federation of Soft Computing
    • Agence de Développement Economique de Cergy-Pontoise
    • The European Neural Network Society
    • Comité d'Expansion Economique du Val d'Oise

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    New York, NY, United States

    Publication History

    Published: 28 October 2008

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    Author Tags

    1. distributed consensus
    2. emergent semantics
    3. multi-agent system
    4. peer-to-peer computing
    5. random networks

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    View all
    • (2014)IoT-aided robotics applicationsComputer Communications10.1016/j.comcom.2014.07.01354:C(32-47)Online publication date: 1-Dec-2014
    • (2013)Learning by Gossip: A Principled Information Exchange Model in Social NetworksCognitive Computation10.1007/s12559-013-9211-65:3(327-339)Online publication date: 9-Mar-2013

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