3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems

Research Article

Association in Multi-agent Simulations of Dynamic Random Social Networks

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  • @INPROCEEDINGS{10.4108/ICST.BIONETICS2008.4742,
        author={Rob Stocker and Henry Larkin},
        title={Association in Multi-agent Simulations of Dynamic Random Social Networks},
        proceedings={3d International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems},
        publisher={ICST},
        proceedings_a={BIONETICS},
        year={2010},
        month={5},
        keywords={Multi-agent systems social networks simulation complex systems.},
        doi={10.4108/ICST.BIONETICS2008.4742}
    }
    
  • Rob Stocker
    Henry Larkin
    Year: 2010
    Association in Multi-agent Simulations of Dynamic Random Social Networks
    BIONETICS
    ICST
    DOI: 10.4108/ICST.BIONETICS2008.4742
Rob Stocker1,2,*, Henry Larkin1,2,*
  • 1: UNSW@ADFA, School of IT & EE
  • 2: Defence and Security Applications Research Centre, UNSW@ADFA, Canberra ACT Australia +61 2 6268 8157
*Contact email: r.stocker@adfa.edu.au, h.larkin@adfa.edu.au

Abstract

Social groups form where individuals who are attracted to each other - usually by a common interest – interact and form clusters. These groups exist within structural networks that rely on the patterns of links between members through which communication and resource transfer occurs. Individual influence impacts on emergent characteristics of a group, for example, global opinion and collective behaviour. However, individuals join and leave groups, thus changing the system’s dynamics. What impact do these structural changes have on the emergence of sub-groups? Here our interest is in the association of members around a particular ideology and real social network systems provide our bio-inspired simulation models. We address the effects of dynamic structural changes to randomly connected networks on global behaviour and the emergence of subgroups that associate with specific states. Results from multi-agent simulations demonstrate that social cohesion and collection of nodes around particular states are dependent on group dynamics and can have an impact on social management that effects social order and stability.