Abstract
The collective knowledge increase, in general, is understood as an additional amount of knowledge in a collective in comparison with the average of the knowledge states given by collective members on the same subject in the real world. These knowledge states reflect the real knowledge state of the subject, but only to some degree because of the incompleteness and uncertainty. In this work, we investigate the influence of the inconsistency degree on the collective knowledge increase in a collective by taking into account the number of collective members. In addition, by means of experiments we prove that the amount of knowledge increase in a collective with higher inconsistency degree is better than that in a collective with lower inconsistency degree.
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This research is partially funded by Vietnam National University Ho Chi Minh City (VNU-HCM) under grant number C2014-26-05.
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Nguyen, V.D., Nguyen, N.T. (2016). Some Novel Results of Collective Knowledge Increase Analysis Using Euclidean Space. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9693. Springer, Cham. https://doi.org/10.1007/978-3-319-39384-1_30
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DOI: https://doi.org/10.1007/978-3-319-39384-1_30
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