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[2602.21268] A Dynamic Survey of Soft Set Theory and Its Extensions
Summary
This article provides a comprehensive overview of soft set theory and its various extensions, highlighting key definitions, constructions, and current developments in the field.
Why It Matters
Soft set theory offers a structured approach to decision modeling under uncertainty, making it relevant for researchers and practitioners in artificial intelligence and related fields. The survey of its extensions showcases the theory's versatility and applicability across different mathematical domains.
Key Takeaways
- Soft set theory is crucial for parameterized decision modeling.
- Numerous extensions of soft set theory have emerged, enhancing its applicability.
- The theory connects to various mathematical areas, including topology and matroid theory.
Computer Science > Artificial Intelligence arXiv:2602.21268 (cs) [Submitted on 24 Feb 2026] Title:A Dynamic Survey of Soft Set Theory and Its Extensions Authors:Takaaki Fujita, Florentin Smarandache View a PDF of the paper titled A Dynamic Survey of Soft Set Theory and Its Extensions, by Takaaki Fujita and Florentin Smarandache View PDF Abstract:Soft set theory provides a direct framework for parameterized decision modeling by assigning to each attribute (parameter) a subset of a given universe, thereby representing uncertainty in a structured way [1, 2]. Over the past decades, the theory has expanded into numerous variants-including hypersoft sets, superhypersoft sets, TreeSoft sets, bipolar soft sets, and dynamic soft sets-and has been connected to diverse areas such as topology and matroid theory. In this book, we present a survey-style overview of soft sets and their major extensions, highlighting core definitions, representative constructions, and key directions of current development. Comments: Subjects: Artificial Intelligence (cs.AI) MSC classes: 03E72, 03E75 Cite as: arXiv:2602.21268 [cs.AI] (or arXiv:2602.21268v1 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2602.21268 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Takaaki Fujita [view email] [v1] Tue, 24 Feb 2026 11:58:45 UTC (1,648 KB) Full-text links: Access Paper: View a PDF of the paper titled A Dynamic Survey of Soft Set Theory and Its Extens...
