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Consensus Reaching Processes under Hesitant Linguistic Assessments

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Intelligent Systems'2014

Abstract

In this paper, we introduce a flexible consensus reaching process when agents evaluate the alternatives through linguistic expressions formed by a linguistic term, when they are confident on their opinions, or by several consecutive linguistic terms, when they hesitate. Taking into account an appropriate metric on the set of linguistic expressions and an aggregation function, a degree of consensus is obtained for each alternative. An overall degree of consensus is obtained by combining the degrees of consensus on the alternatives by means of an aggregation function. If that overall degree of consensus reaches a previously fixed threshold, then a voting system is applied. Otherwise, a moderator initiates a consensus reaching process by inviting some agents to modify their assessments in order to increase the consensus.

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References

  1. Agell, N., Sánchez, G., Sánchez, M., Ruiz, F.J.: Selecting the best taste: a group decision-making application to chocolates design. In: Proceedings of the 2013 IFSA-NAFIPS Joint Congress, Edmonton, pp. 939–943 (2013)

    Google Scholar 

  2. Alcalde-Unzu, J., Vorsatz, M.: Measuring the cohesiveness of preferences: an axiomatic analysis. Social Choice and Welfare 41, 965–988 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  3. Alcantud, J.C.R., de Andrés, R., Cascón, J.M.: On measures of cohesiveness under dichotomous opinions: some characterizations of Approval Consensus Measures. Information Sciences 240, 45–55 (2013)

    Article  MathSciNet  Google Scholar 

  4. Balinski, M., Laraki, R.: A theory of measuring, electing and ranking. Proceedings of the National Academy of Sciences of the United States of America 104, 8720–8725 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  5. Balinski, M., Laraki, R.: Majority Judgment. Measuring, Ranking, and Electing. The MIT Press, Cambridge (2011)

    Book  Google Scholar 

  6. Beliakov, G., Pradera, A., Calvo, T.: Aggregation Functions: A Guide for Practitioners. STUDFUZZ, vol. 221. Springer, Heidelberg (2007)

    Google Scholar 

  7. Bordogna, G., Fedrizzi, M., Pasi, G.: A linguistic modeling of consensus in group decision making based on OWA operators. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans 27, 126–133 (1997)

    Article  Google Scholar 

  8. Bosch, R.: Characterizations of Voting Rules and Consensus Measures. Ph. D. Dissertation, Tilburg University (2005)

    Google Scholar 

  9. Cabrerizo, F.J., Moreno, J.M., Pérez, I.J., Herrera-Viedma, E.: Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks. Soft Computing 14, 451–463 (2010)

    Article  Google Scholar 

  10. Cabrerizo, F.J., Pérez, I.J., Herrera-Viedma, E.: Managing the consensus in group decision making in an unbalanced fuzzy linguistic context with incomplete information. Knowledge-Based Systems 23, 169–181 (2010)

    Article  Google Scholar 

  11. Eklund, P., Rusinowska, A., de Swart, H.: Consensus reaching in committees. European Journal of Operational Research 178, 185–193 (2007)

    Article  MATH  Google Scholar 

  12. Erdamar, B., García-Lapresta, J.L., Pérez-Román, D., Sanver, M.R.: Measuring consensus in a preference-approval context. Information Fusion 17, 14–21 (2014)

    Article  Google Scholar 

  13. Falcó, E., García-Lapresta, J.L., Roselló, L.: Aggregating imprecise linguistic expressions, in: P. Guo and W. Pedrycz (Eds.), Human-Centric Decision-Making Models for Social Sciences. Springer-Verlag, Berlin, pp. 97-113 (2014)

    Google Scholar 

  14. Falcó, E., García-Lapresta, J.L., Roselló, L.: Allowing agents to be imprecise: A proposal using multiple linguistic terms. Information Sciences 258, 249–265 (2014)

    Article  MathSciNet  Google Scholar 

  15. Fedrizzi, M., Kacprzyk, J., Nurmi, H.: Consensus degrees under fuzzy majorities and fuzzy preferences using OWA (ordered weighted average) operators. Control and Cybernetics 22, 71–80 (1993)

    MathSciNet  Google Scholar 

  16. Fedrizzi, M., Kacprzyk, J., Owsińnski, J.W., Zadrozny, S.: Consensus reaching via a GDSS with fuzzy majority and clustering of preference profiles. Annals of Operations Research 51, 127–139 (1994)

    Article  MATH  Google Scholar 

  17. Fedrizzi, M., Kacprzyk, J., Zadrozny, S.: An interactive multi-user decision support system for consensus reaching processes using fuzzy logic with linguistic quantifiers. Decision Support Systems 4, 313–327 (1988)

    Article  Google Scholar 

  18. García-Lapresta, J.L.: Favoring consensus and penalizing disagreement in group decision making. Journal of Advanced Computational Intelligence and Intelligent Informatics 12(5), 416–421 (2008)

    Google Scholar 

  19. García-Lapresta, J.L., Aldavero, C., de Castro, S.: A linguistic approach to multi-criteria and multi-expert sensory analysis. In: Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (eds.) IPMU 2014, Part II. CCIS, vol. 443, pp. 586–595. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  20. García-Lapresta, J.L., Pérez-Román, D.: Measuring consensus in weak orders. In: Herrera-Viedma, E., García-Lapresta, J.L., Kacprzyk, J., Fedrizzi, M., Nurmi, H., Zadrożny, S. (eds.) Consensual Processes. STUDFUZZ, vol. 267, pp. 213–234. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  21. García-Lapresta, J.L., Pérez-Román, D.: Consensus-based clustering under hesitant qualitative assessments. Fuzzy Sets and Systems (in press), doi:10.1016/j.fss, 05.0040165-0114

    Google Scholar 

  22. Gini, C.: Variabilità e Mutabilità. Tipografia di Paolo Cuppini, Bologna (1912)

    Google Scholar 

  23. Grabisch, M., Marichal, J.L., Mesiar, R., Pap, E.: Aggregation Functions. Cambridge University Press, Cambridge (2009)

    Book  MATH  Google Scholar 

  24. Herrera, F., Herrera-Viedma, E., Verdegay, J.L.: A model of consensus in group decision making under linguistic assessments. Fuzzy Sets and Systems 78, 73–87 (1996)

    Article  MathSciNet  Google Scholar 

  25. Herrera, F., Herrera-Viedma, E., Verdegay, J.L.: Linguistic measures based on fuzzy coincidence for reaching consensus in group decision making. International Journal of Approximate Reasoning 16, 309–334 (1997)

    Article  MATH  Google Scholar 

  26. Herrera-Viedma, E., Herrera, F., Chiclana, F.: A consensus model for multiperson decision making with different preference structures. IEEE Transactions on Systems, Man and Cybernetics - Part A: Systems and Humans 32, 394–402 (2002)

    Article  Google Scholar 

  27. Kacprzyk, J., Fedrizzi, M.: ‘Soft’ consensus measures for monitoring real consensus reaching processes under fuzzy preferences. Control and Cybernetics 15, 309–323 (1986)

    MathSciNet  Google Scholar 

  28. Kacprzyk, J., Fedrizzi, M.: A ‘soft’ measure of consensus in the setting of partial (fuzzy) preferences. European Journal of Operational Research 34, 315–325 (1988)

    Article  MathSciNet  Google Scholar 

  29. Kacprzyk, J., Fedrizzi, M.: A ‘human-consistent’ degree of consensus based on fuzzy logic with linguistic quantifiers. Mathematical Social Sciences 18, 275–290 (1989)

    Article  MATH  MathSciNet  Google Scholar 

  30. Kacprzyk, J., Fedrizzi, M., Nurmi, H.: Group decision making and consensus under fuzzy preferences and fuzzy majority. Fuzzy Sets and Systems 49, 21–31 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  31. Martínez, L., Montero, J.: Challenges for improving consensus reaching process in collective decisions. New Mathematics and Natural Computation 3, 203–217 (2007)

    Article  MATH  Google Scholar 

  32. Martínez-Panero, M.: Consensus perspectives: Glimpses into theoretical advances and applications. In: Herrera-Viedma, E., García-Lapresta, J.L., Kacprzyk, J., Fedrizzi, M., Nurmi, H., Zadrożny, S. (eds.) Consensual Processes. STUDFUZZ, vol. 267, pp. 179–193. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  33. Mata, F., Martínez, L., Herrera-Viedma, E.: An adaptive consensus support model for group decision-making problems in a multigranular fuzzy linguistic context. IEEE Transactions on Fuzzy Systems 17, 279–290 (2009)

    Article  Google Scholar 

  34. Mata, F., Pérez, L.G., Zhou, S.M., Chiclana, F.: Type-1 OWA methodology to consensus reaching processes in multi-granular linguistic contexts. Knowledge-Based Systems 58, 11–22 (2014)

    Article  Google Scholar 

  35. Palomares, I., Estrella, F.J., Martínez, L., Herrera, F.: Consensus under a fuzzy context: taxonomy, analysis framework AFRYCA and experimental case of study. Information Fusion 20, 252–271 (2014)

    Article  Google Scholar 

  36. Palomares, I., Martínez, L.: A semi-supervised multi-agent system model to support consensus reaching processes. IEEE Transactions on Fuzzy Systems (in press), doi:10.1109/TFUZZ.2013.2272588

    Google Scholar 

  37. Palomares, I., Martínez, L., Herrera, F.: A consensus model to detect and manage noncooperative behaviors in large-scale group decision making. IEEE Transactions on Fuzzy Systems 22(3), 516–530 (2014)

    Article  Google Scholar 

  38. Pérez, I.J., Cabrerizo, F.J., Alonso, S., Herrera-Viedma, E.: A new consensus model for group decision making problems with non homogeneous experts. IEEE Transactions on Systems, Man, and Cybernetics: Systems 44, 494–498 (2014)

    Article  Google Scholar 

  39. Pérez, I.J., Wikström, R., Mezei, J., Carlsson, C., Herrera-Viedma, E.: A new consensus model for group decision making using fuzzy ontology. Soft Computing 17, 1617–1627 (2013)

    Article  Google Scholar 

  40. Roselló, L., Prats, F., Agell, N., Sánchez, M.: Measuring consensus in group decisions by means of qualitative reasoning. International Journal of Approximate Reasoning 51, 441–452 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  41. Roselló, L., Prats, F., Agell, N., Sánchez, M.: A qualitative reasoning approach to measure consensus. In: Herrera-Viedma, E., García-Lapresta, J.L., Kacprzyk, J., Fedrizzi, M., Nurmi, H., Zadrożny, S. (eds.) Consensual Processes. STUDFUZZ, vol. 267, pp. 235–261. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  42. Roselló, L., Sánchez, M., Agell, N., Prats, F., Mazaira, F.A.: Using consensus and between generalized multiattribute linguistic assessments for group decision-making. Information Fusion 17, 83–92 (2014)

    Article  Google Scholar 

  43. Saint, S., Lawson, J.R.: Rules for Reaching Consensus. A Modern Approach to Decision Making. Jossey-Bass, San Francisco (1994)

    Google Scholar 

  44. Spillman, B., Bezdek, J., Spillman, R.: Development of an instrument for the dynamic measurement of consensus. Communication Monographs 46, 1–12 (1979)

    Article  Google Scholar 

  45. Torra, V., Narukawa, Y.: Modeling Decisions: Information Fusion and Aggregation Operators. Springer, Berlin (2007)

    Google Scholar 

  46. Travé-Massuyès, L., Dague, P. (eds.): Modèles et Raisonnements Qualitatifs. Hermes Science, Paris (2003)

    Google Scholar 

  47. Travé-Massuyès, L., Piera, N.: The orders of magnitude models as qualitative algebras. In: Proceedings of the 11th International Joint Conference on Artificial Intelligence, Detroit (1989)

    Google Scholar 

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Correspondence to José Luis García-Lapresta .

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García-Lapresta, J.L., Pérez-Román, D., Falcó, E. (2015). Consensus Reaching Processes under Hesitant Linguistic Assessments. In: Angelov, P., et al. Intelligent Systems'2014. Advances in Intelligent Systems and Computing, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-319-11313-5_24

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  • DOI: https://doi.org/10.1007/978-3-319-11313-5_24

  • Publisher Name: Springer, Cham

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