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The need of fairness in group consensus reaching process in a fuzzy environment

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
PL
Koncepcja „sprawiedliwości” w procesie osiągania konsensusu w grupie w warunkach rozmytości
Języki publikacji
EN
Abstrakty
EN
In this paper we explain the need of "fairness" in the human-consistent computational system which supports a group consensus reaching process. We propose the model which combines mathematical approach based on fuzzy environment, i.e. “soft” consensus developed by Kacprzyk and Fedrizzi and socio-psychological approach concerning fairness component. We view fairness from two possible perspectives: a fair distribution and a fair final decision. Finally, we confirm our assumptions by observations in the analyzed groups of students.
PL
W niniejszym artykule wyjaśniono potrzebę „sprawiedliwości” w systemie obliczeniowym wspomagającym proces osiągania konsensusu w grupie decydentów. Autorki zaproponowały model łączący podejście matematyczne oparte na środowisku rozmytym oraz czynniki społeczno-psychologiczne wyjaśniające opisywaną koncepcję. Pojęcie „sprawiedliwości” rozpatrywane jest tu w dwóch kategoriach: rozkładu zasobów oraz decyzji ostatecznej. Założenia poparte są wnioskami na podstawie obserwacji grup studentów.
Rocznik
Strony
29--38
Opis fizyczny
Bibliogr. 20 poz.
Twórcy
  • Department of Automatic Control and InformationTechnology, Faculty of Electrical and Computer Engineering, Cracow University of Technology
autor
  • Department of Automatic Control and Information Technology, Faculty of Electrical and Computer Engineering, Cracow University of Technology
Bibliografia
  • [1] Camerer C.F., Psychology and economics. Strategizing in the brain, Science, 300, 2003, 1673-1675.
  • [2] Center for Excellence in Government, Facilitator’s Toolbox, 1996, http://www.employeesu.com/docs/EmployeeResources/Creating%20Consensus.pdf, [date of access: 23.03.13].
  • [3] Falkiewicz D., Kacprzyk J., Different Aspects of Supporting Group Consensus Reaching Process Under Fuzzines, Technical Transactions, vol. 1-AC/2012, Cracow University of Technology Press, 17-27.
  • [4] Fedrizzi M., Kacprzyk J., Zadrożny S., An interactive multi-user decision support system for consensus reaching process using fuzzy logic with linguistic quantifiers, Decision Support Systems, vol. 4, no. 3, 1988, 313-327.
  • [5] Fehr E., Schmidt K., A Theory of Fairness, Competition and Cooperation, The Quarterly Journal of Economics, MIT Press, no. 3, vol. 114, 1999, 817-868.
  • [6] Hanson S.O., Decision Theory: A Brief Introduction, Philosophy, vol. 23, Royal Institute of Technology, Stockholm, 1994, 1-94.
  • [7] Jennings H.H., Sociometric differentiation of the psychegroup and sociogroup, Sociometry, vol. 10, 1947, 71-79.
  • [8] Kacprzyk J., Neuroeconomics: yet another field where rough sets can be useful?, Chac C.C et al. (Eds.): RSCTC 2008, LNCS, vol. 5306, 2008, 1-12.
  • [9] Kacprzyk J., Fedrizzi M., A ‘human-consistent’ degree of consensus based on fuzzy logic with linguistic quantifiers, Mathematical Social Sciences, vol. 18, 1989, 275-290.
  • [10] Kacprzyk J., Fedrizzi M., A ‘soft’ measure of consensus in the setting of partial (fuzzy) preferences, European Journal of Operational Research, vol. 34, 1988, 315-325.
  • [11] Kacprzyk J., Zadrożny S., On a concept of a consensus reaching process support system based on the use of soft computing and Web techniques, [in:] D. Ruan, J. Montero, J. Lu, L. Martínez, P. D’hondt, E.E. Kerre (Eds.): Computational Intelligence in Decision and Control. World Scientific, 2008, 859-864.
  • [12] Kacprzyk J., Zadrożny S., Soft computing and Web intelligence for supporting consensus reaching, Soft Computing, vol. 14, no. 8, 2010, 833-846.
  • [13] Kacprzyk J., Zadrożny S., Supporting Consensus Reaching Processes under Fuzzy Preferences and a Fuzzy Majority via Linguistic Summaries, Preferences and Decisions Studies in Fuzziness and Soft Computing, Springer, vol. 257, 2010, 261-279.
  • [14] Kacprzyk J., Zadrożny S., Raś Z., How to Support Consensus Reaching Using Action Rules: a Novel Approach, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, World Scientific, vol. 18, no. 4, 2010, 451-470.
  • [15] Priem R.L., Harrison D.A., Muir N.K., Structured Conflict and Consensus Outcomes in Group Decision Making, Journal of Management, 1995, vol. 21, no. 4, 691-710.
  • [16] Turban E., Aronson J.E., Liang T.P., Decision Support Systems and Intelligent Systems, 6th Edition, Prentice Hall, 11-19, 2005, 94-101.
  • [17] Tyler T.R., Smith H.J., The handbook of social psychology, vol. 2, Social justice and social movements, McGraw-Hill, Boston, 1998, 595-629.
  • [18] Wierzbicki A., Trust and Fairness in Open, Distributed Systems, Springer, 2010, 11-19, 56-70.
  • [19] Young H.P., Equity: In Theory and Practice, Princeton University Press, 1994.
  • [20] Zadeh, L, A computational approach to fuzzy quantifiers in natural languages, Computers and Mathematics with Applications, no. 9, 1983, 149-184.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a00fabc3-6d42-4816-aa09-7c8b103b2253
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