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SDML: A Multi-Agent Language for Organizational Modelling

Author

Listed:
  • Scott Moss

    (Manchester Metropolitan University)

  • Helen Gaylard

    (Manchester Metropolitan University)

  • Steve Wallis

    (Manchester Metropolitan University)

  • Bruce Edmonds

    (Manchester Metropolitan University)

Abstract

A programming language which is optimized for modelling multi-agent interaction within articulated social structures such as organizations is described with several examples of its functionality. The language is SDML, a strictly declarative modelling language which has object-oriented features and corresponds to a fragment of strongly grounded autoepistemic logic. The virtues of SDML include the ease of building complex models and the facility for representing agents flexibly as models of cognition as well as modularity and code reusability. Two representations of cognitive agents within organizational structures are reported and a Soar-to-SDML compiler is described. One of the agent representations is a declarative implementation of a Soar agent taken from the Radar-Soar model of Ye and Carley (1995). The Ye-Carley results are replicated but the declarative SDML implementation is shown to be much less computationally expensive than the more procedural Soar implementation. As a result, it appears that SDML supports more elaborate representations of agent cognition together with more detailed articulation of organizational structure than we have seen in computational organization theory. Moreover, by representing Soar-cognitive agents declaratively within SDML, that implementation of the Ye-Carley specification is necessarily consistent and sound with respect to the formal logic to which SDML corresponds.

Suggested Citation

  • Scott Moss & Helen Gaylard & Steve Wallis & Bruce Edmonds, 1998. "SDML: A Multi-Agent Language for Organizational Modelling," Computational and Mathematical Organization Theory, Springer, vol. 4(1), pages 43-69, March.
    • Handle: RePEc:spr:comaot:v:4:y:1998:i:1:d:10.1023_a:1009600530279
    DOI: 10.1023/A:1009600530279
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    References listed on IDEAS

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    1. Helen Gaylard, 1997. "A Re-analysis of the Effects of Task Decomposition and Organizational Structure on Performance and Robustness," Discussion Papers 97-29, Manchester Metropolitan University, Centre for Policy Modelling.
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    Cited by:

    1. Catholijn M. Jonker & Martijn C. Schut & Jan Treur & Pınar Yolum, 2007. "Analysis of meeting protocols by formalisation, simulation, and verification," Computational and Mathematical Organization Theory, Springer, vol. 13(3), pages 283-314, September.
    2. J. Gareth Polhill & Dawn C. Parker & Daniel Brown & Volker Grimm, 2008. "Using the ODD Protocol for Describing Three Agent-Based Social Simulation Models of Land-Use Change," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-3.
    3. Adolfo Lopez Paredes & Cesáreo Hernández Iglesias, 1999. "Beyond Experimental Economics: Trading Institutions and Multiagent Systems," Computing in Economics and Finance 1999 1351, Society for Computational Economics.
    4. Scott Moss, 2000. "Canonical Tasks, Environments and Models for Social Simulation," Computational and Mathematical Organization Theory, Springer, vol. 6(3), pages 249-275, September.
    5. Oswaldo Terán & Johanna Alvarez & Magdiel Ablan & Manuel Jaimes, 2007. "Characterising Land Holding Size Distributions in a Forest Reserve," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 1-6.
    6. Bruce Edmonds, 1999. "Gossip, Sexual Recombination and the El Farol Bar: Modelling the Emergence of Heterogeneity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 2(3), pages 1-2.
    7. Lopez-Paredes, Adolfo & Hernandez-Iglesias, Cesareo & Gutierrez, Javier Pajares, 2002. "Towards a new experimental socio-economics: Complex behaviour in bargaining," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 31(4), pages 423-429.

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