Weighted Group Role Assignment Based on Three-Way Conflict Analysis With Interval-Valued Intuitionistic Fuzzy Numbers
针对角色重要性差异化、能力评估不确定性和冲突分类缺失三个问题，提出基于区间直觉模糊数的三支冲突分析方法，实现加权群组角色分配，并通过实验验证有效性。
Role-based collaboration (RBC) has become a crucial computational approach for task allocation and team coordination, yet three critical research gaps remain unresolved. First, while existing methods treat role importance uniformly, real-world scenarios require differentiated prioritization of roles, which is a gap addressed through role weight vectors that dynamically adjust task significance. Second, current qualification matrices that directly specify agent capabilities lack mechanisms to handle assessment uncertainties, leading this article to propose a novel determination method using intuitionistic fuzzy numbers for robust capability modeling. Third, the absence of systematic conflict categorization frameworks motivates our three-way conflict analysis (TWCA) method that classifies conflicts through hierarchical comparisons of agent competency. Drawing from these considerations, the article presents the weighted group role assignment (GRA) with conflicting constraints problem, aiming to overcome the identified challenges through environments-classes, agents, roles, groups, and objects (E-CARGO) framework. The proposed approach is tested and validated through a series of experiments and comparative analyses to demonstrate its efficacy.