Abstract
This paper investigates properties of implicative weights and the use of implicative weights in evaluation criteria. We analyze and compare twelve different forms of implication and compare them with multiplicative weights and exponential weights that are also used in evaluation criteria. Since weighted conjunction is based on implicative weights, we also investigate the usability of weighted conjunction in evaluation criteria.
The original version of this chapter has been revised: Minor errors in the text have been corrected. The correction to this chapter is available at https://doi.org/10.1007/978-3-030-00202-2_26
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Change history
15 November 2018
The original versions of chapters “Graded Logic Aggregation” and “Implicative Weights as Importance Quantifiers in Evaluation Criteria” have been revised; minor errors in the text have been corrected at the request of the author.
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Torra, V. (2018). Implicative Weights as Importance Quantifiers in Evaluation Criteria. In: Torra, V., Narukawa, Y., Aguiló, I., González-Hidalgo, M. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2018. Lecture Notes in Computer Science(), vol 11144. Springer, Cham. https://doi.org/10.1007/978-3-030-00202-2_16
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DOI: https://doi.org/10.1007/978-3-030-00202-2_16
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