Fuzzy Information Evolution with Three-Way Decision in Social Network Group Decision-Making

2025-05-22

AI Summary

Addressing fuzziness, dynamic social structures, and subjective information modeling in group decision-making remains challenging. Method: This paper proposes a multi-agent framework integrating three-way decision theory, dynamic network reconstruction, and linguistic opinion representation. It introduces three-way decisions into social network-based group decision-making for the first time, explicitly modeling individual hesitation and cognitive uncertainty; designs an adaptive link-adjustment rule based on opinion similarity to enable co-evolution of network topology and opinion dynamics. The approach unifies three-way decision theory, dynamic social network modeling, linguistic uncertainty representation, multi-agent simulation, and consensus analysis. Contribution/Results: Evaluated in a multi-UAV collaborative decision-making scenario, the framework significantly improves system stability and consensus attainment rate, while more realistically capturing human-like behaviors—including hesitation, dynamic opinion revision, and relational evolution—during collective decision processes.

Technology Category

• Multiagent Systems: Agreement, Argumentation & Negotiation
• Humans and AI: Planning and Decision Support for Human-Machine Teams
• Reasoning under Uncertainty: Decision/Utility Theory

Application Category

• Social Networks and Social Media: Media and governance, opinion dynamics, filter bubbles, polarization
• User Modeling, Personalization and Recommendation: Social recommender systems and personalization for the social Web
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In group decision-making (GDM) scenarios, uncertainty, dynamic social structures, and vague information present major challenges for traditional opinion dynamics models. To address these issues, this study proposes a novel social network group decision-making (SNGDM) framework that integrates three-way decision (3WD) theory, dynamic network reconstruction, and linguistic opinion representation. First, the 3WD mechanism is introduced to explicitly model hesitation and ambiguity in agent judgments, thereby preventing irrational decisions. Second, a connection adjustment rule based on opinion similarity is developed, enabling agents to adaptively update their communication links and better reflect the evolving nature of social relationships. Third, linguistic terms are used to describe agent opinions, allowing the model to handle subjective, vague, or incomplete information more effectively. Finally, an integrated multi-agent decision-making framework is constructed, which simultaneously considers individual uncertainty, opinion evolution, and network dynamics. The proposed model is applied to a multi-UAV cooperative decision-making scenario, where simulation results and consensus analysis demonstrate its effectiveness. Experimental comparisons further verify the advantages of the algorithm in enhancing system stability and representing realistic decision-making behaviors.

Problem

• Address uncertainty in social network group decision-making
• Model dynamic social structures and opinion evolution
• Handle vague information using linguistic representation

Innovation

• Three-way decision models hesitation in judgments
• Dynamic network updates via opinion similarity
• Linguistic terms handle vague information effectively