Equilibrium solutions for multiobjective bimatrix games incorporating fuzzy goals

Equilibrium solutions in terms of a degree of attainment of a fuzzy goal for games in fuzzy and multiobjective environments are examined. The authors introduce a fuzzy goal for a payoff in order to incorporate ambiguity of human judgments and assume that a player tries to maximize his degree of attainment of the fuzzy goal. A fuzzy goal for a payoff and the equilibrium solution with respect to a degree of attainment of a fuzzy goal are defined. Two basic methods, one by weighting coefficients and the other by a minimum component, are employed to aggregate multiple fuzzy goals. When membership functions are linear functions, the computational methods for the equilibrium solutions are developed. It is shown that the equilibrium solutions are equal to optimal solutions of mathematical programming problems in both cases. The relation between equilibrium solutions for multiobjective bimatrix games incorporating fuzzy goals and the Pareto optimal equilibrium solutions are considered. [In Japanese.]