def testEquilibriumSelectionPD(self):
a_pd = BimatrixTwoStrategyGame(
-1.0, -1.0, -4.0, 0.0, 0.0, -4.0, -3.0, -3.0)
# equilibrium is unique
self.assertEqual(len(a_pd.find_nash()), 1)
# D,D
self.assertTrue(a_pd.find_unique_equilibrium() == (0.0, 0.0))
# no risk dominant
try:
a_pd.find_risk_dominant_equilibrium(atol=10e-3)
except NoEquilibriumSelected:
self.assertTrue(True)
else:
self.assertTrue(False)
def testEquilibriumSelectionCoordinationGame(self):
a_coordination_game = BimatrixTwoStrategyGame(
1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0)
self.assertEqual(len(a_coordination_game.find_nash()), 3)
self.assertEqual(
a_coordination_game.find_unique_equilibrium(), (0.5, 0.5))
def testUniqueEquilibrium(self):
game_with_unique_equilibrium = BimatrixTwoStrategyGame(
a1=1, a2=4, b1=3, b2=3, c1=2, c2=2, d1=4, d2=1)
self.assertEqual(1, len(game_with_unique_equilibrium.find_nash()))
