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In continuous game theory problems without analytical solutions, numerical methods have to be applied. As the number of players grows, this may increase computational costs due to the curse of dimensionality. Chebyshev multidimensional interpolation allows efficient multiple evaluations simultaneously along several dimensions (tensorization), and the algorithms can be adapted to handle parallel computation. Both properties can be employed to reduce the computational time cost. Value and Policy iteration are two well-known techniques from Control Theory that can be applied in differential game problems. Employing multidimensional Chebyshev interpolation, both Value and Policy Iteration based methods can be implemented and their performance, pros and cons compared. (Joint work with Carmelo de Castro and Beatriz Gómez-Martín)