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Różnorodne aspekty wspierania procesu osiągania konsensusu w grupie w warunkach rozmytości
Języki publikacji
Abstrakty
In this paper we present human-consistent approach of multi-model consensus reaching process supporting by group decision support systems. We consider the idea developed by Kacprzyk and Zadrożny [9, 10, 12] which is related to the “soft” consensus, and where the core of the system is based on fuzzy logic. Essentially, we attempt to stress the multi-model architecture of considering system and distinguish several aspects, i.e. model of agent, model of moderator, model of consensus achievement. Moreover, we present a novel concept based on fair consensus as a meaningful point of further development.
W niniejszym artykule zaprezentowano wybrane aspekty złożonego procesu osiągania konsensusu nadzorowanego przez systemy wspierające podejmowanie decyzji w grupie. Rozważono ideę opracowaną przez Kacprzyka i Zadrożnego [9, 10, 12] powiązaną z terminem „miękkiego” konsensus, opartą na logice rozmytej. Przedstawiono złożoną architekturę rozważanego systemu oraz rozróżniono w nim kilka aspektów, tj. model agenta, model moderatora, model osiągania konsensusu. Ponadto, zaprezentowano nową koncepcję opartą na sprawiedliwym konsensusie jako punkt wyjścia dla dalszych badań.
Czasopismo
Rocznik
Tom
Strony
17--27
Opis fizyczny
Bibliogr. 21 poz., rys., wz.
Twórcy
autor
- Katedra Automatyki i Technik Informacyjnych, Wydział Inżynierii Elektrycznej i Komputerowej, Politechnika Krakowska
autor
- Katedra Automatyki i Technik Informacyjnych, Wydział Inżynierii Elektrycznej i Komputerowej, Politechnika Krakowska
- Instytut Badań Systemowych, Polska Akademia Nauk
Bibliografia
- [1] 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.
- [2] Hansson S.O., Decision Theory: A Brief Introduction, Royal Institute of Technology (KTH), Stockholm 2005, revision, http://home.abe.kth.se/~soh/decisiontheory.pdf (date of access: 01.07.2012).
- [3] Herrera F., Herrera-Viedma E., Verdegay J.L., A model of consensus in group decision making under linguistic assessment, Fuzzy Sets and Systems, vol. 78, 1996, 73-87.
- [4] Jennings H.H., Sociometric differentiation of the psychegroup and sociogroup, Sociometry, vol. 10, 1947, 71-79.
- [5] Kacprzyk J., Multistage Decision Making in Fuzzy Conditions (in Polish), PWN,Warsaw 1983.
- [6] 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.
- [7] 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.
- [8] Kacprzyk J., Yager R.R., Zadrożny S., Fuzzy linguistic summaries of databases for an efficient business data analysis and decision support, W. Abramowicz, J. Żurada (Eds.): Knowledge Discovery for Business Information Systems, 2001, 129-152.
- [9] Kacprzyk J., Zadrożny S., Protoforms of Linguistic Database Summaries as a Human Consistent Tool for Using Natural Language in Data Mining, Database Technologies: Concepts, Methodologies, Tools and Applications, 2009, 1038-1049.
- [10] Kacprzyk J., Zadrożny S., Soft computing and Web intelligence for supporting consensus reaching, Soft Computing, vol. 14, No. 8, 2010, 833-846.
- [11] 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, vol. 18, No. 4, 2010, 451-470.
- [12] Kacprzyk J., Zadrożny S., Raś Z., Supporting consensus reaching process under fuzzy preferences and a fuzzy majoraty via linquistic summaries and action rules, Studies in Fuziness and Soft Computing, vol. 267, 2011, 289-314.
- [13] Ogryczak W., Fair and efficient resource allocation, Bicriteria Models for Equitable Optimization, ICINCO 2008 Fifth International Conference on Informatics in Control, Automation and Robotics, 2008, 149-156.
- [14] Ogryczak W., Multicriteria models for fair resource allocation, Control and Cybernetics, vol. 36, no. 2, 2007, 303-332.
- [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] Regan H.M., Colyvan M., Markovchick-Nicholls L., A formal model for consensus and negotiation in environmental management, Journal of Environmental Management 80, 2006, 167-176.
- [17] Sprague R.H.Jr., A Framework for the Development of Decision Support Systems, Management Information Systems Quarterly, vol. 4, No. 4, 1980, 1-26
- [18] What is a Group Decision Support System (GDSS)?, Decision Support Systems Resources, http://www.dssresources.com/ (date of access: 10.07.2012).
- [19] Yager R.R., Linguistic summaries as a tool for database discovery, FUZZ-IEEE’95/IFES’95, Workshopon Fuzzy Database Systems and Information Retrieval, 1995, 79-82.
- [20] Yager R.R., On ordered weighted averaging operators in multicriteria decision making, IEEE Transactions on Systems, Man and Cybernetics, SMC-18, 1988, 183-190.
- [21] Zadeh L.A., A computational approach to fuzzy quantifiers in natural languages, Computers and mathematics with Applications, vol. 9, No. 1, 1983, 149-184.
Uwagi
EN
Dominika Falkiewicz’s contribution is partially supported by the Foundation for Polish Science under International PhD Projects in Intelligent Computing. Project financed from The European Union within the Innovative Economy Operational Programme 2007–2013 and European Regional Development Fund.
Typ dokumentu
Bibliografia
Identyfikator YADDA
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