A Rule-based Approach for Modelling Behaviour in Crisis and Emergency Scenarios

  • Antonio De Nicola
  • Giordano Vicoli
  • Maria Luisa Villani
Conference paper
Part of the Proceedings of the I-ESA Conferences book series (IESACONF, volume 5)

Abstract

Crisis management is a critical task requiring a deep knowledge of the related scenario where usually interoperability and collaboration among different services and actors take place. To support crisis management a promising approach is based on simulation and analysis. Precondition to them is the possibility to model both structural and behavioural aspects of the addressed domain. In a previous paper we presented the CEML domain specific language to model structural aspects of a crisis scenario. Here we focus on behavioural aspects and we present the CEML behavioural modeling framework to model them. This framework consists of the CEML language and an incremental method to specify behaviour based on the stimulus-response model, the event-condition-action rules, and the Reaction RuleML language.

Keywords

Crisis management Behavioural modeling Reaction rules 

Notes

Acknowledgement

This work has been partly funded by the European Commission through the Project MOTIA (JLS/2009/CIPS/AG/C1-016).

References

  1. 1.
    Martí, J.R., Ventura, C.E., et al.. “I2Sim Mod. and Sim. Framework for Scenario Development, Training, and Real-Time Decision Support of Multiple Interdependent Critical Infrastructures during Large Emergencies”, NATO, RTA/MSG Conf. on “How is Mod. and Sim. Meeting the Defence Challenges Out to 2015?”, 2008.Google Scholar
  2. 2.
    De Nicola A., Tofani A., Vicoli G., Villani M.L.. “Modeling Collaboration for Crisis and Emergency Management”, COLLA 2011 Int. Conference, 2011.Google Scholar
  3. 3.
    OMG-MDA, “MDA Guide, version 1.0.1,” Available at: http://www.omg.org/mda/presentations.htm, 2003. Retrieved on 20th September 2011.
  4. 4.
    Simon H. A., “The Sciences of the Artificial”, The MIT Press. 3rd ed. 1996.Google Scholar
  5. 5.
    Dittrich K. R., Gatziu S., Geppert A.. “The Active Database Management System Manifesto: A Rulebase of ADBMS Features”, LNCS 985, Springer, 1995.Google Scholar
  6. 6.
    Paschke, A., Kozlenkov, A., Boley, H.. “A Homogenous Reaction Rule Language for Complex Event Processing”, 2nd EDA-PS Workshop, Austria, 2007.Google Scholar
  7. 7.
  8. 8.
    Lee E. A.. “Finite State Machines and Modal Models in Ptolemy II”, Technical report, EECS Department, University of California, Berkeley, UCB/EECS-2009-151, 2009.Google Scholar
  9. 9.
    Tisue, S., Wilensky, U. “NetLogo: A simple environment for modeling complexity”. In Int. Conf. on Complex Systems, 2004.Google Scholar
  10. 10.
    Gabriel A. Wainer and Pieter Mosterman Eds.. “Discrete-Event Modeling and Simulation: Theory and Applications”, 1st ed., CRC Press, 2010.Google Scholar
  11. 11.
    OMG-SysML, “OMG Systems Modeling Language” version 1.2. Available at: http://www.omgsysml.org/. 2010.
  12. 12.
    Warmer J. and Kleppe A., “The Object Constraint Language: Getting Your Models Ready for MDA”, Addison-Wesley, 2003.Google Scholar
  13. 13.
    Kifer M., “Rule Interchange Format: The Framework”, LNCS 5341, Springer, 2008.Google Scholar
  14. 14.
    Friedman-Hill, E.. “Jess in Action”, Manning, Greenwich, CT, 2003.Google Scholar
  15. 15.
    Browne, P.: “JBoss Drools Business Rules”. Packt Publishing, 2009.Google Scholar

Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  • Antonio De Nicola
    • 1
  • Giordano Vicoli
    • 1
  • Maria Luisa Villani
    • 1
  1. 1.ENEARomaItaly

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