def pure_equilibria(game, *, epsilon=0):
"""Returns an array of all pure nash profiles"""
eqa = [
prof for prof in game.profiles()
if regret.pure_strategy_regret(game, prof) <= epsilon
]
return np.stack(eqa) if eqa else np.empty((0, game.num_strats))
def test_pure_incomplete_data():
"""Test pure regret with incomplete data"""
profiles = [[2, 0]]
payoffs = [[1.0, 0.0]]
game = paygame.game(2, 2, profiles, payoffs)
reg = regret.pure_strategy_regret(game, [2, 0])
assert np.isnan(reg), 'regret of missing profile not nan'
def test_pure_prisoners_dilemma(_):
"""Test pure prisoners dilemma"""
game = gamegen.sym_2p2s_game(2, 0, 3, 1) # prisoners dilemma
eqm = [0, 2]
assert regret.pure_strategy_regret(game, eqm) == 0, \
'Known equilibrium was not zero regret'
def min_regret_profile(game):
"""Finds the profile with the confirmed lowest regret
An error will be raised if there are no profiles with a defined regret.
"""
regs = np.fromiter((regret.pure_strategy_regret(game, prof)
for prof in game.profiles), float, game.num_profiles)
return game.profiles[np.nanargmin(regs)]
def pure_nash(game, epsilon=0):
"""Returns an array of all pure nash profiles"""
eqa = [prof[None] for prof in game.profiles
if regret.pure_strategy_regret(game, prof) <= epsilon]
if eqa:
return np.concatenate(eqa)
else:
return np.empty((0, game.num_role_strats))
def min_regret_profile(game):
"""Finds the profile with the confirmed lowest regret
An error will be raised if there are no profiles with a defined regret.
"""
utils.check(not game.is_empty(), 'Game must have a profile')
reg, _, prof = min(
(_nan_to_inf(regret.pure_strategy_regret(game, prof)), i, prof)
for i, prof in enumerate(game.profiles()))
utils.check(not np.isinf(reg), 'No profiles had valid regret')
return prof
def min_regret_profile(game):
"""Finds the profile with the confirmed lowest regret
An error will be raised if there are no profiles with a defined regret.
"""
utils.check(not game.is_empty(), 'Game must have a profile')
reg, _, prof = min(
(_nan_to_inf(regret.pure_strategy_regret(game, prof)), i, prof)
for i, prof in enumerate(game.profiles()))
utils.check(not np.isinf(reg), 'No profiles had valid regret')
return prof
def reg(game, serial, prof):
"""the regret of the profile"""
if is_pure_profile(game, prof):
return regret.pure_strategy_regret(game, prof).item()
else:
return regret.mixture_regret(game, prof).item()
def calc_reg(game, prof):
"""the regret of the profile"""
if is_pure_profile(game, prof): # pylint: disable=no-else-return
return regret.pure_strategy_regret(game, np.asarray(prof, int)).item()
else:
return regret.mixture_regret(game, prof).item()
def test_pure_incomplete_data():
profiles = [[2, 0]]
payoffs = [[1.0, 0.0]]
game = rsgame.Game(2, 2, profiles, payoffs)
reg = regret.pure_strategy_regret(game, [2, 0])
assert np.isnan(reg), "regret of missing profile not nan"
def pure_equilibria(game, *, epsilon=0):
"""Returns an array of all pure nash profiles"""
eqa = [prof for prof in game.profiles()
if regret.pure_strategy_regret(game, prof) <= epsilon]
return np.stack(eqa) if eqa else np.empty((0, game.num_strats))
