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This paper introduces to the computational techniques of non-cooperative bimatrix games in an uncertain environment. Both single and multiple objective fuzzy-valued bimatrix games are considered theoretically with one numerical example. The presentation is centered on the Nishizaki and Sakawa models. These models are based on the maxmin and minmax principles of the classical matrix game theory. Equivalent nonlinear (possibly quadratic) programming problems are giving optimal solutions. The equilibrium solutions correspond to players trying to maximize a degree of attainment of the fuzzy goals. The aggregation of all the fuzzy sets in the multiobjective models use the fuzzy decision rule by Bellman and Zadeh. This 'aggregation by a minimum component' consists in the intersection of the fuzzy sets, the fuzzy expected payoffs and the fuzzy goals. Numerical examples of two-players nonzero sum games are solved using the Mathematica software. The numerical solutions are possibly using iterative methods.