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Supporting the Harvard Model of Principled Negotiation with Superexpertise

  • Xenogene Gray
  • Pamela Noel Gray
  • John Zeleznikow
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 97)

Abstract

An expert epistemology is a theory about knowledge in the expertise and includes knowledge representation, semantics, specifications, heuristics, reasoning, etc. Superexpert systems employ computer capabilities to extend ordinary human abilities, and are derived from expert epistemologies. A superexpert system, Negotiation Game or NeGame (NeG), is designed to support the Harvard Principled Negotiation model; it is illustrated by a Civilisation application which reframes the Israel-Palestine conflict as the task of negotiating a mutually acceptable civilisation. The negotiation epistemology of NeG evolved from the adversarial epistemology of eGanges (eG); both handle tasks in a user-friendly and transparent way. NeG manages hierarchical complexity of the conflict issues and differences in their subjective values, advises on cumulative scoring of Wins and Losses, and, through mathematical techniques, maximises Win-Win options. Adversarial epistemology requires four-valued logic, whereas negotiation epistemology requires six-valued logic; they share a common knowledge hierarchy, called a River.

Keywords

epistemology superexpertise eGanges Principled Negotiation quality control fishbone 

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References

  1. 1.
    Gray, P.: Legal Knowledge Engineering Methodology for Large Scale Expert Systems, Volumes 1 and 2, PhD thesis, University of Western Sydney (2007), http://trove.nla.gov.au/work/3901700
  2. 2.
    Gray, P., Gray, X.: A map-based expert-friendly shell. In: Bourcier, D. (ed.) Legal Knowledge and Information Systems. IOS Press, Amsterdam (2003)Google Scholar
  3. 3.
    Fraunce, A.: The lawyer’s logic, Reproduced from the original manuscript in the British Museum, Lawiers Logike, first published by William How, London, The Scolar Press Limited, Menston, Yorkshire, England (originally published 1588, 1969) Google Scholar
  4. 4.
    Gray, P.N., Mann, S.: The Fraunce (1588) model of case-based reasoning. In: Proceedings of 9th International Conference on Artificial Intelligence and Law. ACM, New York (2003)Google Scholar
  5. 5.
    Ong, W.J.: Ramus method and the decay of dialogue. Harvard University Press, Cambridge (1958)Google Scholar
  6. 6.
    Fisher, R., Ertel, D.: Getting Ready to Negotiate. Penguin, New York (1995)Google Scholar
  7. 7.
    Fisher, R., Ury, W., Patton, B.: Getting to Yes. Random Century, London (1991)Google Scholar
  8. 8.
    Spencer, D.: Essential Dispute Resolution, Cavendish Australia, Sydney (2005)Google Scholar
  9. 9.
    Mayer, B.: The Dynamics of Conflict Resolution. Jossey-Bass, San Francisco (2000)Google Scholar
  10. 10.
    Zeleznikow, J., Bellucci, E.: Classifying Online Dispute Resolution by comparing family mediation and the Israel – Palestinian conflict. In: Proceedings of 13th International Conference on Artificial Intelligence and Law. ACM, New York (2011)Google Scholar
  11. 11.
    Gray, P., Gray, X.: Quality Controlled Government with Spherical Logic. Int. J. Interdisciplinary Soc. Sci. 5(10), 271–284 (2011), http://iji.cgpublisher.com/product/pub.88/prod.1305 Google Scholar
  12. 12.
    Menkel-Meadow, C.: Toward another view of legal negotiation: the structure of problem solving. University of California Law Review 31, 755 (1984)Google Scholar
  13. 13.
    Ishikawa, K.: What is total quality control? The Japanese way, translated by David J. Lu. Prentice-Hall Inc., Englewood Cliffs (1985)Google Scholar
  14. 14.
    Blyth, T.S.: Lattices and Ordered Algebraic Structures. Springer, San Francisco (2005)Google Scholar
  15. 15.
    Lukasiewicz: O logice trojwartosciowej (On three-valued logic). Ruch filozoficzny 5, 170–171 (1920)Google Scholar
  16. 16.
    Kleene, S.C.: Introduction to Metamathematics. North Holland, Amsterdam (1952)Google Scholar
  17. 17.
    Belnap, N.: How a computer should think. In: Ryle, G. (ed.) Contemporary Aspects of Philosophy, pp. 30–55. Oriel Press, Stocksfield (1976)Google Scholar
  18. 18.
    Ginsberg, M.L.: Multivalued logics: A uniform approach to inference in artificial intelligence. Computational Intelligence 4(3), 256–316 (1992)Google Scholar
  19. 19.
    Fitting, M.: Many-valued non-monotonic modal logics. In: Nerode, A., Taitslin, M.A. (eds.) LFCS 1992. LNCS, vol. 620, pp. 139–150. Springer, Heidelberg (1992)CrossRefGoogle Scholar
  20. 20.
    Majkić, Z.: Ontological encapsulation of many-valued logic. In: Proceedings of Convegno Italiano di Logica Computazionale (2004), http://www.cs.unipr.it/CILC04/DownloadArea/Majkic-CILC04.pdf

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Xenogene Gray
    • 1
  • Pamela Noel Gray
    • 2
  • John Zeleznikow
    • 3
  1. 1.Department of Computing, Faculty of ScienceMacquarie UniversityAustralia
  2. 2.Centre for Research in Complex SystemsCharles Sturt UniversityBathurstAustralia
  3. 3.Laboratory of Decision Support and Dispute Management, School of Management and Information SystemsVictoria UniversityMelbourneAustralia

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