conflict_level
- negmas.preferences.conflict_level(u1, u2, outcomes, max_tests=10000)[source]
Finds the conflict level in these two ufuns
- Parameters
u1 (
UtilityFunction
) – first utility functionu2 (
UtilityFunction
) – second utility function
Examples
A nonlinear strictly zero sum case
>>> from negmas.preferences.crisp.mapping import MappingUtilityFunction >>> from negmas.preferences import conflict_level >>> outcomes = [(_,) for _ in range(10)] >>> u1 = MappingUtilityFunction(dict(zip(outcomes, ... np.random.random(len(outcomes))))) >>> u2 = MappingUtilityFunction(dict(zip(outcomes, ... 1.0 - np.array(list(u1.mapping.values()))))) >>> print(conflict_level(u1=u1, u2=u2, outcomes=outcomes)) 1.0
The same ufun
>>> print(conflict_level(u1=u1, u2=u1, outcomes=outcomes)) 0.0
A linear strictly zero sum case
>>> outcomes = [(i,) for i 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)))) >>> print(conflict_level(u1=u1, u2=u2, outcomes=outcomes)) 1.0
- Return type