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Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems - A User Study

Razak, T.R., Garibaldi, J.M., Wagner, C., Pourabdollah, A., Soria, D. (2019) Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems - A User Study. In: Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. . pp. 420-426. (doi:10.1109/SSCI.2018.8628924) (KAR id:98870)

Abstract

In recent years, researchers have become increasingly more interested in designing an interpretable Fuzzy Logic System (FLS). Many studies have claimed that reducing the complexity of FLSs can lead to improved model interpretability. That is, reducing the number of rules tends to reduce the complexity of FLSs, thus improving their interpretability. However, none of these studies have considered interpretability and complexity from human perspectives. Since interpretability is of a subjective nature, it is essential to see how people perceive interpretability and complexity particularly in relation to creating FLSs. Therefore, in this paper we have investigated this issue using an initial user study. This is the first time that a user study has been used to assess the interpretability and complexity of designs in relation to creating FLSs. The user study involved a range of expert practitioners in FLSs and received a diverse set of answers. We are interested to see whether, from the perspectives of people, FLSs are necessarily more interpretable when they are less complex in terms of their design. Although the initial user study is based on small samples (i.e., 25 participants), nevertheless this research provides initial insight into this issue that motivates our future research. © 2018 IEEE.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/SSCI.2018.8628924
Additional information: cited By 15
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Daniel Soria
Date Deposited: 07 Dec 2022 15:17 UTC
Last Modified: 09 Dec 2022 19:25 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/98870 (The current URI for this page, for reference purposes)

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