def test_nash_value_sequence_form_lp(self):
"""Checks Nash value using a Python sequence form LP solver."""
game = pyspiel.load_game("python_kuhn_poker")
val1, val2, _, _ = sequence_form_lp.solve_zero_sum_game(game)
# value from Kuhn 1950 or https://en.wikipedia.org/wiki/Kuhn_poker
self.assertAlmostEqual(val1, -1 / 18)
self.assertAlmostEqual(val2, +1 / 18)
def test_leduc_poker(self):
game = pyspiel.load_game("leduc_poker")
val1, val2, _, _ = sequence_form_lp.solve_zero_sum_game(game)
# values obtained from Appendix E.2 of Lanctot et al. 2017, A Unified
# Game-Theoretic Approach to Multiagent Reinforcement Learning.
# https://arxiv.org/abs/1711.00832
self.assertAlmostEqual(val1, -0.085606424078, places=6)
self.assertAlmostEqual(val2, 0.085606424078, places=6)
def test_iigoofspiel4(self):
game = pyspiel.load_game_as_turn_based("goofspiel", {
"imp_info": True,
"num_cards": 4,
"points_order": "descending",
})
val1, val2, _, _ = sequence_form_lp.solve_zero_sum_game(game)
# symmetric game, should be 0
self.assertAlmostEqual(val1, 0)
self.assertAlmostEqual(val2, 0)
def test_kuhn_poker(self):
game = pyspiel.load_game("kuhn_poker")
val1, val2, _, _ = sequence_form_lp.solve_zero_sum_game(game)
# value from Kuhn 1950 or https://en.wikipedia.org/wiki/Kuhn_poker
self.assertAlmostEqual(val1, -1 / 18)
self.assertAlmostEqual(val2, +1 / 18)
def test_rock_paper_scissors(self):
game = pyspiel.load_game_as_turn_based("matrix_rps")
val1, val2, _, _ = sequence_form_lp.solve_zero_sum_game(game)
self.assertAlmostEqual(val1, 0)
self.assertAlmostEqual(val2, 0)
