Abstract
This chapter concludes the book by summarizing the main conclusions derived from the LGDM research advances and pending challenges to date. Some proposed directions for future research in this topic are finally highlighted.
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References
Palomares, I., Martinez, L.: A semisupervised multiagent system model to support consensus-reaching processes. IEEE Transactions on Fuzzy Systems, 22(4), pp. 762–777, 2014.
Palomares, I., Martínez, L., Herrera, F.: A consensus model to detect and manage non-cooperative behaviors in large-scale group decision making. IEEE Transactions on Fuzzy Systems, 22(3), pp. 516–530, 2014.
Palomares, I., Martínez, L., Herrera, F.: MENTOR: A graphical monitoring tool of preferences evolution in large-scale group decision making. Knowledge-based Systems, 58 (Spec.Iss.), pp. 66–74, 2014.
Shi, Z.J., Wang, X.Q., Palomares, I., Guo, S.J., Ding, R.X.: A novel consensus model for multi-attribute large-scale group decision making based on comprehensive behavior Classification and adaptive weight updating. Knowledge-based Systems, In Press. https://doi.org/10.1016/j.knosys.2018.06.002
Zhang, H., Palomares, I., Dong, Y., Wang, W.: Managing non-cooperative behaviors in consensus-based multiple attribute group decision making: An approach based on social network analysis. Knowledge-based Systems, In press. https://doi.org/10.1016/j.knosys.2018.06.008
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Palomares Carrascosa, I. (2018). Conclusions and Future Directions of Research. In: Large Group Decision Making. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-030-01027-0_6
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DOI: https://doi.org/10.1007/978-3-030-01027-0_6
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