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Qualitative risk assessment fulfils a need

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Applications of Uncertainty Formalisms

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1455))

Abstract

Classically, risk is characterised by a point value probability indicating the likelihood of occurrence of an adverse effect. However, there are domains where the attainability of objective numerical risk characterisations is increasingly being questioned. This paper reviews the arguments in favour of extending classical techniques of risk assessment to incorporate meaningful qualitative and weak quantitative risk characterisations. A technique in which linguistic uncertainty terms are defined in terms of patterns of argument is then proposed. The technique is demonstrated using a prototype computer-based system for predicting the carcinogenic risk due to novel chemical compounds.

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10 References

  1. J. Adams. Risk. UCL Press, London, 1995.

    Google Scholar 

  2. J. Ashby. Benzyl acetate: from mutagenic carcinogen to non-mutagenic non-carcinogen in 7 years?. Mutation Res., 306:107–109, 1994.

    Article  Google Scholar 

  3. J. Ashby and R.W. Tennant. Definitive relationships among chemical structure, carcinogenicity and mutagenicity for 301 chemicals tested by the U.S. NTP. Mutation Res., 257:229–306, 1991.

    Article  Google Scholar 

  4. S. Benferhat, C. Cayrol, D. Dubois, J. Lang and H. Prade. Inconsistency management and prioritized syntax-based entailment. Proc. International Joint Conference on Artificial Intelligence’ 93, Chambery, France, 1993.

    Google Scholar 

  5. P. Brown. Quoted in Local Transport Today (30 October), 1991.

    Google Scholar 

  6. D.V. Budescu and T.S. Wallsten. A Review of Human Linguistic Probability Processing. Knowledge Engineering Review, 10:43–62, 1995.

    Article  Google Scholar 

  7. R.L. Carter. Guidelines for the Evaluation of Chemicals for Carcinogenicity. London: HMSO, 1991.

    Google Scholar 

  8. D. Dubois and H. Prade. Non-standard theories of uncertainty in knowledge representation and reasoning. Knowledge Engineering Review, 9:399–416, 1994.

    Article  Google Scholar 

  9. M. Elvang-Gøransson, P.J. Krause and J. Fox. Dialectic reasoning with inconsistent information. In: Heckerman, D. and Mamdani, A. (eds.), Uncertainty in Artificial Intelligence. Proceedings of the Ninth Conference, San Mateo Ca: Morgan Kaufmann, 1993.

    Google Scholar 

  10. J. Fox. Language, Logic and Uncertainty. Technical Report, Imperial Cancer Research Fund, London, 1984.

    Google Scholar 

  11. J. Fox. Three arguments for extending the framework of probability. In: Kanal L.H. and Lemmer J.F. (eds), Uncertainty in Artificial Intelligence, Elsevier Science Publishers B.V. (North-Holland), 1986.

    Google Scholar 

  12. J. Fox and P.J. Krause. Symbolic decision theory and autonomous agents. In: D’Ambrosio B.D., Smets P. and Bonissone P.P., Uncertainty in Artificial Intelligence, Proceedings of the Seventh Conference, San Mateo Ca: Morgan Kaufmann, 1991.

    Google Scholar 

  13. J. Fox, P.J. Krause and S.J. Ambler. Arguments, contradictions and practical reasoning. Proceedings of ECAI’ 92, John Wiley and Sons, 623–627, 1992.

    Google Scholar 

  14. J. Fox and P.J. Krause. Formal Definitions of Arguments and Cases. ICRF Technical Report, 1994.

    Google Scholar 

  15. P.J. Krause, J. Fox and P. Judson. An Argumentation Based Approach to Risk Assessment, IMA Journal of Mathematics Applied in Business and Industry, 5: 249–263, 1994.

    MATH  Google Scholar 

  16. P.J. Krause, S.J. Ambler, M. Elvang-Gøransson and J. Fox. A Logic of Argumentation for Reasoning under Uncertainty. Computational Intelligence, 11:113–131, 1995.

    Article  MathSciNet  Google Scholar 

  17. R.P. Loui. Defeat among arguments: a system of defeasible inference. Computational Intelligence, 3:100–106, 1987.

    Article  Google Scholar 

  18. National Research Council. Risk Assessment in the Federal Government: Managing the Process. Washington DC: National Academy Press, 1992.

    Google Scholar 

  19. D. Nute. Defeasible Reasoning and Decision Support Systems. Decision Support Systems, 4:97–110, 1988.

    Article  Google Scholar 

  20. S. Parsons. Normative argumentation and qualitative probability. Proceedings of the International Joint Conference on Practical Reasoning, Bonn, 1997.

    Google Scholar 

  21. D.L. Poole. On the comparison of theories: preferring the most specific explanation. Proc. IJCAI’ 85, Los Angeles, USA, 144–147, 1985.

    Google Scholar 

  22. Roy. Soc. Risk: Analysis, Perception & Management. London: The Royal Society, 1992.

    Google Scholar 

  23. D.M. Sanderson and C.G. Earnshaw. Computer Prediction of Possible Toxic Action from Chemical Structure; The DEREK System. Human & Experimental Toxicology, 10:261–273, 1991.

    Article  Google Scholar 

  24. U.S. EPA. Guidelines for Carcinogen Risk Assessment. Federal Register, 51, 33991–34003, 1986.

    Google Scholar 

  25. U.S. FDA. General principles for evaluating the safety of compounds used in food-producing animals. Appendix 1. Carcinogen structure guide. Washington: U.S. Food and Drug Administration, 1986.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Imperial Cancer Research Fund, London, WC2A 3PX, UK

    Paul Krause & John Fox

  2. Judson Consulting Service, Heather Lea, Norwood, Harrogate, HG3 1TE, UK

    Philip Judson

  3. LHASA UK Ltd., School of Chemistry, University of Leeds, LS2 9JT, Leeds, UK

    Mukesh Patel

Authors
  1. Paul Krause
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  2. John Fox
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  3. Philip Judson
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  4. Mukesh Patel
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK

    Anthony Hunter

  2. Queen Mary and Westfield College, Department of Electronic Engineering, University of London, London, E1 4NS, UK

    Simon Parsons

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© 1998 Springer-Verlag Berlin Heidelberg

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Krause, P., Fox, J., Judson, P., Patel, M. (1998). Qualitative risk assessment fulfils a need. In: Hunter, A., Parsons, S. (eds) Applications of Uncertainty Formalisms. Lecture Notes in Computer Science(), vol 1455. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49426-X_7

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  • DOI: https://doi.org/10.1007/3-540-49426-X_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-65312-7

  • Online ISBN: 978-3-540-49426-3

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