New Models of Three-Way Conflict Analysis Based on Decision-Theoretic Rough Sets

Conflict is widespread in society, and trisecting an agent set is a crucial research direction in three-way conflict analysis. In practice, the varying risk preferences among decision-makers lead to diverse trisections of an agent set in similar circumstances. In this paper, we consider decision-makers’ risk preferences and propose novel models of three-way conflict. Initially, we divide a set of issues into two disjoint subsets and utilize information entropy to compute issues’ weights. Then, we design alliance measures regarding an individual issue through the transition probability function. Based on the issues’ weights and alliance measures, we propose alliance probabilities between two agents. Additionally, we present risk-preferred, risk-averse, and risk-neutral decisions with the relative utility function. Finally, we design an algorithm to derive rules for three-way conflict analysis and demonstrate how to utilize the proposed model for decision-making through an example.