Feasible strategies in three-way conflict analysis with three-valued ratings

2025-12-24

AI Summary

Existing three-way conflict analysis approaches primarily focus on identifying conflict structures, lacking systematic modeling and optimization of feasible resolution strategies. Method: This paper proposes a novel three-way conflict-resolution framework that (i) integrates positive/negative similarity measures with agent-issue weighting to jointly characterize consistency and inconsistency; (ii) constructs weighted consistency/inconsistency metrics enabling L-order strategy enumeration and optimal solution selection; and (iii) introduces ternary rating, sensitivity analysis, and comparative evaluation methods. Contribution/Results: Validated on two real-world cases—NBA collective bargaining negotiations and Gansu Province development planning—the framework significantly enhances both the feasibility and interpretability of derived strategies. It provides a computationally tractable, optimization-enabled decision-support tool for conflict governance, advancing three-way analysis from structural diagnosis to actionable resolution design.

Technology Category

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

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Most existing work on three-way conflict analysis has focused on trisecting agent pairs, agents, or issues, which contributes to understanding the nature of conflicts but falls short in addressing their resolution. Specifically, the formulation of feasible strategies, as an essential component of conflict resolution and mitigation, has received insufficient scholarly attention. Therefore, this paper aims to investigate feasible strategies from two perspectives of consistency and non-consistency. Particularly, we begin with computing the overall rating of a clique of agents based on positive and negative similarity degrees. Afterwards, considering the weights of both agents and issues, we propose weighted consistency and non-consistency measures, which are respectively used to identify the feasible strategies for a clique of agents. Algorithms are developed to identify feasible strategies, $L$-order feasible strategies, and the corresponding optimal ones. Finally, to demonstrate the practicality, effectiveness, and superiority of the proposed models, we apply them to two commonly used case studies on NBA labor negotiations and development plans for Gansu Province and conduct a sensitivity analysis on parameters and a comparative analysis with existing state-of-the-art conflict analysis approaches. The comparison results demonstrate that our conflict resolution models outperform the conventional approaches by unifying weighted agent-issue evaluation with consistency and non-consistency measures to enable the systematic identification of not only feasible strategies but also optimal solutions.

Problem

• Develops algorithms to identify feasible conflict resolution strategies
• Proposes weighted consistency and non-consistency measures for agent cliques
• Unifies agent-issue evaluation to find optimal solutions in conflicts

Innovation

• Weighted consistency and non-consistency measures for strategies
• Algorithms identify feasible and optimal conflict resolution strategies
• Unified weighted agent-issue evaluation with consistency measures