International Journal
Year of publication
2017
Volume
6
Pagination
181-194
DOI
10.1007/s13748-016-0108-y
Journal
Progress in Artificial Intelligence
ISSN Number
2192-6360
URL
http://dx.doi.org/10.1007/s13748-016-0108-y
Labella, Á., et al. «Afryca 2.0: An Improved Analysis Framework For Consensus Reaching Processes». Progress In Artificial Intelligence, 2017, pp. 181-194.
Altamente citado
Off
Hot paper
Off
Número especial
Off
International Journal
Year of publication
2016
Publisher
Elsevier
Volume
99
Pagination
71-78
DOI
10.1016/j.knosys.2016.01.047
Journal
Knowledge-Based Systems
Date Published
2016
ISSN Number
0950-7051
URL
http://www.sciencedirect.com/science/article/pii/S0950705116000770
Yejun, X., et al. «Deriving The Priority Weights From Incomplete Hesitant Fuzzy Preference Relations In Group Decision Making». 2016. Knowledge-Based Systems, Elsevier, 2016, pp. 71-78.
Altamente citado
Off
Hot paper
Off
Número especial
Off
Cuartil
Q1
Índice de impacto
4.529
International Journal
Year of publication
2007
Publisher
World Scientific
Volume
3
Pagination
1-15
Journal
New Mathematics and Natural Computation
Number
2
URL
http://www.worldscinet.com/cgi-bin/details.cgi?type=html\&id=pii:S1793005707000720
Martínez, L., y J. Montero. «Challenges For Improving Consensus Reaching Process In Collective Decisions». New Mathematics And Natural Computation, 2, World Scientific, 2007, pp. 1-15.
Altamente citado
Off
Hot paper
Off
Número especial
Off
International Journal
Year of publication
2005
Publisher
IEEE
Volume
13
Pagination
644-658
DOI
10.1109/TFUZZ.2005.856561
Journal
IEEE Transactions on Fuzzy Systems
Number
5
Date Published
10/2005
ISSN Number
1063-6706
URL
http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=1516155\&isnumber=32478
Herrera-Viedma, E., et al. «A Consensus Support System Model For Group Decision-Making Problems With Multi-Granular Linguistic Preference Relations». 10/2005d. C. Ieee Transactions On Fuzzy Systems, 5, IEEE, 2005, pp. 644-658.
Altamente citado
Off
Hot paper
Off
Número especial
Off
Cuartil
1
Índice de impacto
1,88
International Journal
Year of publication
1998
Publisher
Elsevier
Volume
107
Pagination
177-194
Journal
Information Sciences
Number
1
URL
http://www.sciencedirect.com/science?_ob=MImg\&_imagekey=B6V0C-3TKS65B-1R-3\&_cdi=5643\&_user=723053\&_orig=browse\&_coverDate=06\%2F30\%2F1998\&_sk=998929998\&view=c\&wchp=dGLzVtz-zSkzS\&md5=38ae8adc7fe37396a8978ff768794ddf\&ie=/sdarticle.pdf
Delgado, M., et al. «Combining Numerical And Linguistic Information In Group Decision Making». Information Sciences, 1, Elsevier, 1998, pp. 177-194.
Altamente citado
Off
Hot paper
Off
Número especial
Off
International Journal
Year of publication
2012
Publisher
Springer
Volume
16
Pagination
1755-1766
Proyecto
TIN2009-08286
Journal
Soft Computing
Number
10
URL
http://www.springerlink.com/content/p5225p4005832827/?MUD=MP
Palomares, I., et al. «Modelling Experts Attitudes In Group Decision Making». Soft Computing, 10, Springer, 2012, pp. 1755-1766.
Altamente citado
Off
Hot paper
Off
Número especial
Off
International Journal
Year of publication
2009
Publisher
IEEE
Volume
17
Journal
IEEE Transactions on Fuzzy Systems
Number
2
URL
http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=4768682\&isnumber=4808359
Mata, F., et al. «An Adaptive Consensus Support Model For Group Decision-Making Problems In A Multigranular Fuzzy Linguistic Context». Ieee Transactions On Fuzzy Systems, 2, IEEE, 2009.
Altamente citado
Off
Hot paper
Off
Número especial
Off
Year of Publication
2015
Conference Name
XVI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA15), Albacete (Spain), November 9-12th
Castro, J., et al. «Uso De Procesos De Alcance De Consenso Para Mejorar La Recomendación A Grupos». Xvi Conferencia De La Asociación Española Para La Inteligencia Artificial (Caepia15), Albacete (Spain), November 9-12Th, 2015.
National Conference
Altamente citado
Off
Hot paper
Off
Número especial
Off
Resumen
Normally, in group decision making problems, groups are composed by individuals or experts with different goals and points of view. For these reasons, they may adopt distinct behaviors in order to achieve their own aims. Nonetheless, in such problems in general, specially those demanding a certain degree of consensus, each expert should comply with a collaboration contract in order to find a common solution for the decision problem.When decision groups are small, all experts usually attempt to fulfill the collaboration contract. However, nowadays technologies such as social media allow to make consensus-driven decisions with larger groups, in which many experts are involved, hence the possibility that some of them try to break the collaboration contract might be greater. In order to prevent the group solution from being biased by these experts, it is necessary to detect and manage their non-cooperative behaviors in this kind of problems. Recent proposals in the literature suggest managing non-cooperative behavior by reducing the importance of expert opinions. These proposals present drawbacks such as, the inability of an expert to recover his/her importance if behavior improves; and the lack of experts behavior measures across the time. This chapter introduces a methodology based on fuzzy sets and computing with words, with the aim of identifying and managing those experts whose behavior does not contribute to reach an agreement in consensus reaching processes. Such a methodology is characterized by allowing the importance recovery of experts and taking into account the evolution of their behavior across the time.
Year of Publicaion
2015
Volume
10
Pagination
97-121
Publisher
Springer International Publishing
ISBN Number
978-3-319-16828-9
URL
http://dx.doi.org/10.1007/978-3-319-16829-6_5
DOI
10.1007/978-3-319-16829-6_5
Quesada, F. J., et al. Using Computing With Words For Managing Non-Cooperative Behaviors In Large Scale Group Decision Making. Springer International Publishing, 2015, pp. 97-121.
Book Chapter
Hot paper
Off
Altamente citado
Off
Número especial
Off