def __init__(
self,
params: Mapping[str, Any],
network: Optional[dynamic_routing_utils.Network] = None,
vehicles: Optional[List[dynamic_routing_utils.Vehicle]] = None,
perform_sanity_checks: bool = True,
):
"""Initiliaze the game.
Args:
params: game parameters. It should define max_num_time_step and
time_step_length.
network: the network of the game.
vehicles: a list of the vehicle. Their origin and their destination should
be road sections of the game. The number of vehicles in the list sets
the num_players attribute.
perform_sanity_checks: set the perform_sanity_checks attribute.
"""
max_num_time_step = params["max_num_time_step"]
time_step_length = params["time_step_length"]
self.network = network if network else dynamic_routing_data.BRAESS_NETWORK
self._vehicles = (
vehicles
if vehicles else dynamic_routing_data.BRAESS_NETWORK_VEHICLES_DEMAND)
self.network.check_list_of_vehicles_is_correct(self._vehicles)
self.perform_sanity_checks = perform_sanity_checks
self.time_step_length = time_step_length
game_info = pyspiel.GameInfo(
num_distinct_actions=self.network.num_actions(),
max_chance_outcomes=0,
num_players=len(self._vehicles),
min_utility=-max_num_time_step - 1,
max_utility=0,
max_game_length=max_num_time_step)
super().__init__(_GAME_TYPE, game_info, params if params else {})
def __init__(self, params: Mapping[str, Any] = _DEFAULT_PARAMS):
game_info = pyspiel.GameInfo(num_distinct_actions=_NUM_ACTIONS,
max_chance_outcomes=max(
params["size"], _NUM_CHANCE),
num_players=_NUM_PLAYERS,
min_utility=-np.inf,
max_utility=+np.inf,
utility_sum=0.0,
max_game_length=params["horizon"])
super().__init__(_GAME_TYPE, game_info, params)
self.size = params["size"]
self.horizon = params["horizon"]
def __init__(self, params=_DEFAULT_PARAMS):
max_game_length = params["max_game_length"]
super().__init__(
_GAME_TYPE,
pyspiel.GameInfo(num_distinct_actions=2,
max_chance_outcomes=2,
num_players=2,
min_utility=np.min(_PAYOFF) * max_game_length,
max_utility=np.max(_PAYOFF) * max_game_length,
utility_sum=0.0,
max_game_length=max_game_length), params)
self._termination_probability = params["termination_probability"]
def __init__(self, params: Mapping[str, Any] = _DEFAULT_PARAMS):
self.size = get_param("size", params)
self.horizon = get_param("horizon", params)
flat_reward_matrix = np.fromstring(get_param("reward_matrix", params),
dtype=np.float,
sep=" ")
num_players = get_param("players", params)
if len(flat_reward_matrix) != num_players**2:
raise ValueError(
f"Reward matrix passed in flat representation does not represent a "
f"square matrix: {flat_reward_matrix}")
self.reward_matrix = flat_reward_matrix.reshape(
[num_players, num_players])
self.geometry = get_param("geometry", params)
game_info = pyspiel.GameInfo(num_distinct_actions=_NUM_ACTIONS,
max_chance_outcomes=max(
self.size * self.size, _NUM_CHANCE),
num_players=num_players,
min_utility=-np.inf,
max_utility=+np.inf,
utility_sum=0.0,
max_game_length=self.horizon)
super().__init__(_GAME_TYPE, game_info, params)
chance_mode=pyspiel.GameType.ChanceMode.EXPLICIT_STOCHASTIC,
information=pyspiel.GameType.Information.PERFECT_INFORMATION,
utility=pyspiel.GameType.Utility.GENERAL_SUM,
reward_model=pyspiel.GameType.RewardModel.REWARDS,
max_num_players=_NUM_PLAYERS,
min_num_players=_NUM_PLAYERS,
provides_information_state_string=False,
provides_information_state_tensor=False,
provides_observation_string=False,
provides_observation_tensor=False,
provides_factored_observation_string=False,
parameter_specification=_DEFAULT_PARAMS)
_GAME_INFO = pyspiel.GameInfo(num_distinct_actions=2,
max_chance_outcomes=2,
num_players=2,
min_utility=0.,
max_utility=np.inf,
utility_sum=0.0,
max_game_length=9999)
class Action(enum.IntEnum):
COOPERATE = 0
DEFECT = 1
class Chance(enum.IntEnum):
CONTINUE = 0
STOP = 1
dynamics=pyspiel.GameType.Dynamics.SEQUENTIAL,
chance_mode=pyspiel.GameType.ChanceMode.DETERMINISTIC,
information=pyspiel.GameType.Information.PERFECT_INFORMATION,
utility=pyspiel.GameType.Utility.ZERO_SUM,
reward_model=pyspiel.GameType.RewardModel.TERMINAL,
max_num_players=_NUM_PLAYERS,
min_num_players=_NUM_PLAYERS,
provides_information_state_string=True,
provides_information_state_tensor=False,
provides_observation_string=True,
provides_observation_tensor=True,
parameter_specification={})
_GAME_INFO = pyspiel.GameInfo(num_distinct_actions=_NUM_CELLS,
max_chance_outcomes=0,
num_players=2,
min_utility=-1.0,
max_utility=1.0,
utility_sum=0.0,
max_game_length=_NUM_CELLS)
class TicTacToeGame(pyspiel.Game):
"""A Python version of the Tic-Tac-Toe game."""
def __init__(self, params=None):
super().__init__(_GAME_TYPE, _GAME_INFO, params or dict())
def new_initial_state(self):
"""Returns a state corresponding to the start of a game."""
return TicTacToeState(self)
def make_py_observer(self, iig_obs_type=None, params=None):
dynamics=pyspiel.GameType.Dynamics.SEQUENTIAL,
chance_mode=pyspiel.GameType.ChanceMode.EXPLICIT_STOCHASTIC,
information=pyspiel.GameType.Information.IMPERFECT_INFORMATION,
utility=pyspiel.GameType.Utility.ZERO_SUM,
reward_model=pyspiel.GameType.RewardModel.TERMINAL,
max_num_players=_NUM_PLAYERS,
min_num_players=_NUM_PLAYERS,
provides_information_state_string=True,
provides_information_state_tensor=True,
provides_observation_string=True,
provides_observation_tensor=True,
provides_factored_observation_string=True)
_GAME_INFO = pyspiel.GameInfo(
num_distinct_actions=2, # 0 = Pass, 1 = Bet
max_chance_outcomes=3, # The deck has 3 cards
num_players=2,
min_utility=-2.0,
max_utility=2.0,
utility_sum=0.0,
max_game_length=3) # e.g. Pass, Bet, Bet
class KuhnPokerGame(pyspiel.Game):
"""A Python version of Kuhn poker."""
def __init__(self, params=None):
super().__init__(_GAME_TYPE, _GAME_INFO, params or dict())
def new_initial_state(self):
"""Returns a state corresponding to the start of a game."""
return KuhnPokerState(self)
def make_py_observer(self, iig_obs_type=None, params=None):
dynamics=pyspiel.GameType.Dynamics.SEQUENTIAL,
chance_mode=pyspiel.GameType.ChanceMode.EXPLICIT_STOCHASTIC,
information=pyspiel.GameType.Information.IMPERFECT_INFORMATION,
utility=pyspiel.GameType.Utility.ZERO_SUM,
reward_model=pyspiel.GameType.RewardModel.TERMINAL,
max_num_players=_NUM_PLAYERS,
min_num_players=_NUM_PLAYERS,
provides_information_state_string=True,
provides_information_state_tensor=True,
provides_observation_string=True,
provides_observation_tensor=True,
provides_factored_observation_string=True)
_GAME_INFO = pyspiel.GameInfo(num_distinct_actions=len(Action),
max_chance_outcomes=len(_DECK),
num_players=_NUM_PLAYERS,
min_utility=-2.0,
max_utility=2.0,
utility_sum=0.0,
max_game_length=3) # e.g. Pass, Bet, Bet
class KuhnPokerGame(pyspiel.Game):
"""A Python version of Kuhn poker."""
def __init__(self, params=None):
super().__init__(_GAME_TYPE, _GAME_INFO, params or dict())
def new_initial_state(self):
"""Returns a state corresponding to the start of a game."""
return KuhnPokerState(self)
def make_py_observer(self, iig_obs_type=None, params=None):
dynamics=pyspiel.GameType.Dynamics.SEQUENTIAL,
chance_mode=pyspiel.GameType.ChanceMode.DETERMINISTIC,
information=pyspiel.GameType.Information.IMPERFECT_INFORMATION,
utility=pyspiel.GameType.Utility.GENERAL_SUM,
reward_model=pyspiel.GameType.RewardModel.TERMINAL,
max_num_players=_MAX_PLAYERS,
min_num_players=2,
provides_information_state_string=False,
provides_information_state_tensor=True,
provides_observation_string=False,
provides_observation_tensor=False,
provides_factored_observation_string=False)
_GAME_INFO = pyspiel.GameInfo(
num_distinct_actions=_NUM_REGIONS,
max_chance_outcomes=0,
num_players=5,
min_utility=-10.0,
max_utility=10.0,
utility_sum=0.0,
max_game_length=_MAX_PLAYERS)
class CastilloGameState(pyspiel.State):
"""El Grande Castillo Game - subgame of El Grande which decides on the optimum positioning of
pieces moved from the Castillo in the scoring phase of rounds 3/6/9
Parameters:
players - number of players between 1 and 5
rewards - array of 1st/2nd/3rd place triples, one per region
board - string of lowercase alpha characters representing numbers of caballeros per player/region: 'A'==0 and region 0 has castillo cabs
grandes - array of grande region IDs from 1.._NUM_REGIONS
king - region ID of king
"""
dynamics=pyspiel.GameType.Dynamics.MEAN_FIELD,
chance_mode=pyspiel.GameType.ChanceMode.EXPLICIT_STOCHASTIC,
information=pyspiel.GameType.Information.PERFECT_INFORMATION,
utility=pyspiel.GameType.Utility.GENERAL_SUM,
reward_model=pyspiel.GameType.RewardModel.REWARDS,
max_num_players=_NUM_PLAYERS,
min_num_players=_NUM_PLAYERS,
provides_information_state_string=True,
provides_information_state_tensor=False,
provides_observation_string=True,
provides_observation_tensor=True,
parameter_specification=_DEFAULT_PARAMS)
_GAME_INFO = pyspiel.GameInfo(num_distinct_actions=_NUM_ACTIONS,
max_chance_outcomes=max(_SIZE, _NUM_CHANCE),
num_players=_NUM_PLAYERS,
min_utility=-np.inf,
max_utility=+np.inf,
utility_sum=0.0,
max_game_length=_HORIZON)
class MFGCrowdModellingGame(pyspiel.Game):
"""A Mean Field Crowd Modelling game.
A game starts by an initial chance node that select the initial state
of the MFG.
Then the game sequentially alternates between:
- An action selection node (Where the player Id >= 0)
- A Mean Field node (the player id is pyspiel.PlayerId.MEAN_FIELD)
- A chance node (the player id is pyspiel.PlayerId.CHANCE)
