winwin_level

negmas.preferences.winwin_level(u1, u2, outcomes, max_tests=10000)

Finds the win-win level in these two ufuns

Parameters

• u1 (UtilityFunction) – first utility function

• u2 (UtilityFunction) – second utility function

Examples

• A nonlinear same ufun case

>>> from negmas.preferences.crisp.mapping import MappingUtilityFunction
>>> outcomes = [(_,) for _ in range(10)]
>>> u1 = MappingUtilityFunction(dict(zip(outcomes,
... np.linspace(1.0, 0.0, len(outcomes), endpoint=True))))

• A linear strictly zero sum case

>>> outcomes = [(_,) for _ in range(10)]
>>> u1 = MappingUtilityFunction(dict(zip(outcomes,
... np.linspace(0.0, 1.0, len(outcomes), endpoint=True))))
>>> u2 = MappingUtilityFunction(dict(zip(outcomes,
... np.linspace(1.0, 0.0, len(outcomes), endpoint=True))))

Return type

float