An Outcome Preference Information Aggregation Model and Its Algorithm in Hypergame Situations

Abstract

In hypergame situations, it is important for a player to get the more correct opponent players' outcome preference information. In this paper, based on the principle of fuzzy pattern recognition, a nonlinear programming model is established for integrating opponent players' different outcome preference evaluation values perceived by different experts without weight information. An iteration algorithm for solving the model is developed. Using the proposed model and its algorithm, not only the weight of each expert but also the integrated outcome preferences can be obtained easily. A numerical example is provided to illustrate the method.