winwin_level

negmas.preferences.winwin_level(u1: UtilityFunction, u2: UtilityFunction, outcomes: int | Sequence[Outcome], max_tests: int = 10000) → float

Finds the win-win level in these two ufuns.

Parameters:

• u1 – first utility function

• u2 – 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)))
... )