Application of IPK (Information, Preferences, Knowledge) Paradigm for the Modelling of Precautionary Principle Based Decision-Making

  • Adam Maria Gadomski
  • Tomasz Adam Zimny
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5508)


The aim of the article is modelling of the decision-making, in which Precautionary Principle (PP) is applied. Decisions are often made under time constraints, in lack of proper information, preferences or knowledge (IPK). Since application of PP usually bears additional costs, it should be applied only when more efficient risk management policies are unavailable. Presented d-m framework based on the IPK conceptualization allows identification of PP application criteria and models PP as a decisional rule, which is usually applied when the potential threat is recognized, while the risk is not computational, or its assessment is not economically motivated. The proposed model uses the TOGA (Top-down Object-based Goal-oriented Approach) methodology as a modelling tool.


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  1. 1.
    Bingham, J.: Security and Safety in Large Complex Critical Infrastructures (2002) (March 15, 2008),
  2. 2.
    Bologna, S., et al.: Dependability and Survivability in Large Complex Critical Infrastructures. In: Anderson, S., Felici, M., Littlewood, B. (eds.) SAFECOMP 2003. LNCS, vol. 2788, pp. 342–353. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  3. 3.
    COMEST, 2005 - World Commission on the Ethics of Scientific Knowledge and Technology The Precautionary Principle. Paris UNESCOGoogle Scholar
  4. 4.
    Cranor, C.F.: Toward Understanding Aspects of the Precautionary Principle. Journal of Medicine and Philosophy 29(3), 259–279 (2004)CrossRefGoogle Scholar
  5. 5.
    Ezell, B.C.: Infrastructure Vulnerability Assessment Model (I-VAM). Risk Analysis 27(3), 571–583 (2007)CrossRefGoogle Scholar
  6. 6.
    Gadomski, A.M.: TOGA: A methodological and Conceptual Pattern for modeling of Abstract Intelligent Agent. In: Proc. of the First International Round-Table on Abstract Intelligent Agent, January 25-27, 1993, ENEA print (1994)Google Scholar
  7. 7.
    Gadomski, A.M.: TOGA Systemic Approach to the Global Specification. Sophocles Project Report, EU EUREKA (February 12, 2002),
  8. 8.
    Gadomski, A.M.: Socio-Cognitive Engineering Foundations and Applications: From Humans to Nations. Preprints of SCEF 2003 (First International Workshop on Socio-Cognitive Engineering Foundations and Third Abstract Intelligent Agent International Round-Tables Initiative), Rome, September 30 (2003),
  9. 9.
    Gadomski, A.M.: Human organisation socio-cognitive vulnerability: the TOGA meta-theory approach to the modelling methodology. International Journal of Critical Infrastructures 5(1-2), 120–155 (2009)CrossRefGoogle Scholar
  10. 10.
    Gadomski, A.M., et al.: Towards Intelligent Decision Support Systems for Emergency Managers: The IDA Approach. International Journal of Risk Assessment and Management, IJRAM 2(3/4) (2001)Google Scholar
  11. 11.
    Gadomski, A.M., Zimny, T.A.: Risk and Precautionary Principle in Managerial Decision Making: the TOGA Meta-theory Socio-cognitive Perspective. In: CRITIS 2008 Pre-Proceedings, pp. 374–386 (2008)Google Scholar
  12. 12.
    Hahn, W., Sunstein, C.R.: The Precautionary Principle as a basis for decision making. The Economics Voice 2(2) (2005)Google Scholar
  13. 13.
    Haimes, Y.Y.: Total Risk Management. Risk Analysis 11(2), 169–171 (1991)CrossRefGoogle Scholar
  14. 14.
    Haimes, Y.Y.: The Role of the Society for Risk Analysis in the Emerging Threats to Critical Infrastructures. Risk Analysis 19(2), 153–157 (1999)Google Scholar
  15. 15.
    Haimes, Y.Y.: On the Definition of Vulnerabilities in Measuring Risks to Infrastructures. Risk Analysis 2006(2), 293–296 (2006)CrossRefGoogle Scholar
  16. 16.
    Jones, A.: Critical infrastructure protection. Computer fraud & Security 2007(4), 11–15 (2007)CrossRefGoogle Scholar
  17. 17.
    Peterson, M.: The Precautionary Principle Is Incoherent. Risk Analysis 26(3), 595–601 (2006)CrossRefGoogle Scholar
  18. 18.
    Snediker, D.E., Murray, A.T., Matisziw, T.C.: Decision support of network disruption mitigation. Decision Support Systems 44, 954–969 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Adam Maria Gadomski
    • 1
  • Tomasz Adam Zimny
    • 2
  1. 1.Interuniversity Centre ECONA and Italian Research Agency ENEAItaly
  2. 2.Phd candidate, Institute of Legal StudiesPolish Academy of SciencesPoland

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