Feasible strategies for conflict resolution within intuitionistic fuzzy preference-based conflict situations

2026-02-03

AI Summary

This study addresses the limitation of traditional preference conflict models, which only support three qualitative relations—preference, inverse preference, and indifference—and thus fail to capture nuanced agent attitudes toward issues. To overcome this, the paper introduces intuitionistic fuzzy preferences into a three-way conflict analysis framework for the first time, leveraging the fine-grained expressiveness of intuitionistic fuzzy sets to model agent attitudes more precisely. A strategy generation mechanism is developed based on the joint optimization of conflict degree and adjustment magnitude. Through a conflict measure function, a relative loss function, and threshold computation, the approach enables three-way classifications of agent pairs, agent sets, and issue sets. Experimental results demonstrate the effectiveness and practicality of the proposed model in conflict modeling and resolution strategy generation.

Technology Category

• Knowledge Representation and Reasoning: Preferences
• Multiagent Systems: Agreement, Argumentation & Negotiation
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

In three-way conflict analysis, preference-based conflict situations characterize agents'attitudes towards issues by formally modeling their preferences over pairs of issues. However, existing preference-based conflict models rely exclusively on three qualitative relations, namely, preference, converse, and indifference, to describe agents'attitudes towards issue pairs, which significantly limits their capacity in capturing the essence of conflict. To overcome this limitation, we introduce the concept of an intuitionistic fuzzy preference-based conflict situation that captures agents'attitudes towards issue pairs with finer granularity than that afforded by classical preference-based models. Afterwards, we develop intuitionistic fuzzy preference-based conflict measures within this framework, and construct three-way conflict analysis models for trisecting the set of agent pairs, the agent set, and the issue set. Additionally, relative loss functions built on the proposed conflict functions are employed to calculate thresholds for three-way conflict analysis. Finally, we present adjustment mechanism-based feasible strategies that simultaneously account for both adjustment magnitudes and conflict degrees, together with an algorithm for constructing such feasible strategies, and provide an illustrative example to demonstrate the validity and effectiveness of the proposed model.

Problem

• conflict resolution
• intuitionistic fuzzy preference
• three-way conflict analysis
• preference-based conflict
• conflict modeling

Innovation

• intuitionistic fuzzy preference
• three-way conflict analysis
• conflict measures
• adjustment mechanism
• relative loss functions