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Autonomous Learning for Fuzzy Systems: A Review

Gu, Xiaowei, Han, Jungong, Shen, Qiang, Angelov, Plamen (2023) Autonomous Learning for Fuzzy Systems: A Review. Artificial Intelligence Review, 56 (8). pp. 7549-7595. ISSN 0269-2821. E-ISSN 1573-7462. (doi:10.1007/s10462-022-10355-6) (KAR id:98433)

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As one of the three pillars in computational intelligence, fuzzy systems are a powerful mathematical tool widely used for modelling nonlinear problems with uncertainties. Fuzzy systems take the form of linguistic IF-THEN fuzzy rules that are easy to understand for human. In this sense, fuzzy inference mechanisms have been developed to mimic human reasoning and decision-making. From a data analytic perspective, fuzzy systems provide an effective solution to build precise predictive models from imprecise data with great transparency and interpretability, thus facilitating a wide range of real-world applications. This paper presents a systematic review of modern methods for autonomously learning fuzzy systems from data, with an emphasis on the structure and parameter learning schemes of mainstream evolving, evolutionary, reinforcement learning-based fuzzy systems. The main purpose of this paper is to introduce the underlying concepts, underpinning methodologies, as well as outstanding performances of the state-of-the-art methods. It serves as a one-stop guide for readers learning the representative methodologies and foundations of fuzzy systems or who desire to apply fuzzy-based autonomous learning in other scientific disciplines and applied fields.

Item Type: Article
DOI/Identification number: 10.1007/s10462-022-10355-6
Uncontrolled keywords: fuzzy systems; autonomous learning; evolving; evolutionary; reinforcement learning
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Funders: University of Kent (
Depositing User: Xiaowei Gu
Date Deposited: 28 Nov 2022 09:32 UTC
Last Modified: 30 Jun 2023 14:46 UTC
Resource URI: (The current URI for this page, for reference purposes)
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