Research

Multi-level network analysis of multi-agent systems


Reference:

Iravani, P., 2009. Multi-level network analysis of multi-agent systems. In: Iocchi, L., Matsubara, H., Weitzenfeld, A. and Zhou, C., eds. RoboCup 2008: Robot Soccer World Cup XII. Vol. 5399 LNAI. Berlin: Springer, pp. 495-506. (Lecture Notes in Artificial Intelligence, Vol. 5399)

Related documents:

[img]
Preview
Postscript (RBOCUP08IRAVANIFINAL.ps) - Requires a viewer, such as GSview
Download (12MB) | Preview

    Official URL:

    http://dx.doi.org/10.1007/978-3-642-02921-9_43

    Abstract

    This paper presents a multi-level network-based approach to study complex systems formed by multiple autonomous agents. The fundamental idea behind this approach is that elements of a system (represented by network vertices) and their interactions (represented by edges) can be assembled to form structures. Structures are considered to be at one hierarchical level above the elements and interactions that form them, leading to a multi-level organisation. Analysing complex systems represented by multi-level networks make possible the study of the relationships between network topology and dynamics to the system’s global outcome. The framework proposed in this paper is exemplified using data from the RoboCup Football Simulation League.

    Details

    Item Type Book Sections
    CreatorsIravani, P.
    EditorsIocchi, L., Matsubara, H., Weitzenfeld, A. and Zhou, C.
    DOI10.1007/978-3-642-02921-9_43
    Uncontrolled Keywordsmulti agent systems, electric network topology, electric network analysis, autonomous agents, large scale systems
    DepartmentsFaculty of Engineering & Design > Mechanical Engineering
    Research CentresCentre for Power Transmission & Motion Control
    Publisher StatementRBOCUP08IRAVANIFINAL.ps: The original publication is available at www.springerlink.com
    StatusPublished
    ID Code16177
    Additional InformationPaper from RoboCup 2008: Robot Soccer World Cup XII, held in Suzhou, China, 15-18 July 2008

    Export

    Actions (login required)

    View Item

    Document Downloads

    More statistics for this item...