def test_braess_paradox(self):
"""Test that Braess paradox can be reproduced with the mean field game."""
num_player = 8
braess_network = dynamic_routing_utils.Network(
{
"O": "A",
"A": ["B", "C"],
"B": ["C", "D"],
"C": ["D"],
"D": ["E"],
"E": []
},
node_position={
"O": (0, 0),
"A": (1, 0),
"B": (2, 1),
"C": (2, -1),
"D": (3, 0),
"E": (4, 0)
},
bpr_a_coefficient={
"O->A": 0,
"A->B": 1.0,
"A->C": 0,
"B->C": 0,
"B->D": 0,
"C->D": 1.0,
"D->E": 0
},
bpr_b_coefficient={
"O->A": 1.0,
"A->B": 1.0,
"A->C": 1.0,
"B->C": 1.0,
"B->D": 1.0,
"C->D": 1.0,
"D->E": 1.0
},
capacity={
"O->A": num_player,
"A->B": num_player,
"A->C": num_player,
"B->C": num_player,
"B->D": num_player,
"C->D": num_player,
"D->E": num_player
},
free_flow_travel_time={
"O->A": 0,
"A->B": 1.0,
"A->C": 2.0,
"B->C": 0.25,
"B->D": 2.0,
"C->D": 1.0,
"D->E": 0
})
demand = [
dynamic_routing_utils.Vehicle("O->A", "D->E") for _ in range(num_player)
]
game = dynamic_routing.DynamicRoutingGame(
{"time_step_length": 0.125, "max_num_time_step": 40},
network=braess_network,
vehicles=demand)
class TruePathPolicy(policy.Policy):
def __init__(self, game):
super().__init__(game, list(range(num_player)))
self._path = {}
def action_probabilities(self, state, player_id=None):
assert player_id is not None
legal_actions = state.legal_actions(player_id)
if not legal_actions:
return {dynamic_routing_utils.NO_POSSIBLE_ACTION: 1.0}
elif len(legal_actions) == 1:
return {legal_actions[0]: 1.0}
else:
if legal_actions[0] == 2:
if self._path[player_id] in ["top", "middle"]:
return {2: 1.0}
elif self._path[player_id] == "bottom":
return {3: 1.0}
else:
raise ValueError()
elif legal_actions[0] == 4:
if self._path[player_id] == "top":
return {5: 1.0}
elif self._path[player_id] == "middle":
return {4: 1.0}
else:
raise ValueError()
raise ValueError(f"{legal_actions} is not correct.")
class NashEquilibriumBraess(TruePathPolicy):
def __init__(self, game):
super().__init__(game)
for player_id in range(num_player):
if player_id % 2 == 0:
self._path[player_id] = "middle"
if player_id % 4 == 1:
self._path[player_id] = "top"
if player_id % 4 == 3:
self._path[player_id] = "bottom"
class SocialOptimumBraess(NashEquilibriumBraess):
def __init__(self, game):
super().__init__(game)
for player_id in range(num_player):
if player_id % 2 == 0:
self._path[player_id] = "top"
if player_id % 2 == 1:
self._path[player_id] = "bottom"
ne_policy = NashEquilibriumBraess(game)
# TODO(cabannes): debug issue with nash conv computation and uncomment the
# following line.
# self.assertEqual(exploitability.nash_conv(game, ne_policy), 0.0)
self.assertSequenceAlmostEqual(
-expected_game_score.policy_value(game.new_initial_state(), ne_policy),
[3.75] * num_player)
so_policy = SocialOptimumBraess(game)
# TODO(cabannes): debug issue with nash conv computation and uncomment the
# following line.
# self.assertEqual(exploitability.nash_conv(game, so_policy), 0.125)
self.assertSequenceAlmostEqual(
-expected_game_score.policy_value(game.new_initial_state(), so_policy),
[3.5] * num_player)
def setUp(self):
"""Create a network O->A->D for testing."""
super().setUp()
self.network = utils.Network({"O": ["A"], "A": ["D"], "D": []})
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Default data for dynamic routing game."""
from open_spiel.python.games import dynamic_routing_utils
LINE_NETWORK = dynamic_routing_utils.Network({
"bef_O": "O",
"O": ["A"],
"A": ["D"],
"D": ["aft_D"],
"aft_D": []
})
LINE_NETWORK_VEHICLES_DEMAND = [
dynamic_routing_utils.Vehicle("bef_O->O", "D->aft_D") for _ in range(2)
]
LINE_NETWORK_OD_DEMAND = [
dynamic_routing_utils.OriginDestinationDemand("bef_O->O", "D->aft_D", 0,
100)
]
BRAESS_NUM_PLAYER = 5
BRAESS_NETWORK = dynamic_routing_utils.Network(
def create_braess_network(capacity):
graph_dict = {
"A": {
"connection": {
"B": {
"a": 0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": 0
}
},
"location": [0, 0]
},
"B": {
"connection": {
"C": {
"a": 1.0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": 1.0
},
"D": {
"a": 0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": 2.0
}
},
"location": [1, 0]
},
"C": {
"connection": {
"D": {
"a": 0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": 0.25
},
"E": {
"a": 0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": 2.0
}
},
"location": [2, 1]
},
"D": {
"connection": {
"E": {
"a": 1,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": 1.0
}
},
"location": [2, -1]
},
"E": {
"connection": {
"F": {
"a": 0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": 0.0
}
},
"location": [3, 0]
},
"F": {
"connection": {},
"location": [4, 0]
}
}
adjacency_list = {
key: list(value["connection"].keys())
for key, value in graph_dict.items()
}
bpr_a_coefficient = {}
bpr_b_coefficient = {}
capacity = {}
free_flow_travel_time = {}
for o_node, value_dict in graph_dict.items():
for d_node, section_dict in value_dict["connection"].items():
road_section = dynamic_routing_utils._nodes_to_road_section(
origin=o_node, destination=d_node)
bpr_a_coefficient[road_section] = section_dict["a"]
bpr_b_coefficient[road_section] = section_dict["b"]
capacity[road_section] = section_dict["capacity"]
free_flow_travel_time[road_section] = section_dict[
"free_flow_travel_time"]
node_position = {
key: value["location"]
for key, value in graph_dict.items()
}
return dynamic_routing_utils.Network(
adjacency_list,
node_position=node_position,
bpr_a_coefficient=bpr_a_coefficient,
bpr_b_coefficient=bpr_b_coefficient,
capacity=capacity,
free_flow_travel_time=free_flow_travel_time)
def create_sioux_falls_network():
sioux_falls_adjacency_list = {}
sioux_falls_node_position = {}
bpr_a_coefficient = {}
bpr_b_coefficient = {}
capacity = {}
free_flow_travel_time = {}
content = open("./SiouxFalls_node.csv", "r").read()
for line in content.split("\n")[1:]:
row = line.split(",")
sioux_falls_node_position[row[0]] = [
int(row[1]) / 1e5, int(row[2]) / 1e5
]
sioux_falls_node_position[f"bef_{row[0]}"] = [
int(row[1]) / 1e5, int(row[2]) / 1e5
]
sioux_falls_node_position[f"aft_{row[0]}"] = [
int(row[1]) / 1e5, int(row[2]) / 1e5
]
sioux_falls_adjacency_list[f"bef_{row[0]}"] = [row[0]]
sioux_falls_adjacency_list[row[0]] = [f"aft_{row[0]}"]
sioux_falls_adjacency_list[f"aft_{row[0]}"] = []
bpr_a_coefficient[f"{row[0]}->aft_{row[0]}"] = 0.0
bpr_b_coefficient[f"{row[0]}->aft_{row[0]}"] = 1.0
capacity[f"{row[0]}->aft_{row[0]}"] = 0.0
free_flow_travel_time[f"{row[0]}->aft_{row[0]}"] = 0.0
bpr_a_coefficient[f"bef_{row[0]}->{row[0]}"] = 0.0
bpr_b_coefficient[f"bef_{row[0]}->{row[0]}"] = 1.0
capacity[f"bef_{row[0]}->{row[0]}"] = 0.0
free_flow_travel_time[f"bef_{row[0]}->{row[0]}"] = 0.0
content = open("./SiouxFalls_net.csv", "r").read()
for l in content.split("\n")[1:-1]:
_, origin, destination, a0, a1, a2, a3, a4 = l.split(",")
assert all(int(x) == 0 for x in [a1, a2, a3])
sioux_falls_adjacency_list[origin].append(destination)
road_section = f"{origin}->{destination}"
bpr_a_coefficient[road_section] = float(a4)
bpr_b_coefficient[road_section] = 4.0
capacity[road_section] = 1.0
free_flow_travel_time[road_section] = float(a0)
sioux_falls_od_demand = []
content = open("./SiouxFalls_od.csv", "r").read()
for line in content.split("\n")[1:-1]:
row = line.split(",")
sioux_falls_od_demand.append(
dynamic_routing_utils.OriginDestinationDemand(
f"bef_{row[0]}->{row[0]}", f"{row[1]}->aft_{row[1]}", 0,
float(row[2])))
return dynamic_routing_utils.Network(
sioux_falls_adjacency_list,
node_position=sioux_falls_node_position,
bpr_a_coefficient=bpr_a_coefficient,
bpr_b_coefficient=bpr_b_coefficient,
capacity=capacity,
free_flow_travel_time=free_flow_travel_time), sioux_falls_od_demand
def create_series_parallel_network(num_network_in_series,
time_step_length=1,
capacity=1):
i = 0
origin = "A_0->B_0"
graph_dict = {}
while i < num_network_in_series:
tt_up = random.random() + time_step_length
tt_down = random.random() + time_step_length
graph_dict.update({
f"A_{i}": {
"connection": {
f"B_{i}": {
"a": 0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": time_step_length
}
},
"location": [0 + 3 * i, 0]
},
f"B_{i}": {
"connection": {
f"C_{i}": {
"a": 1.0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": tt_up
},
f"D_{i}": {
"a": 1.0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": tt_down
}
},
"location": [1 + 3 * i, 0]
},
f"C_{i}": {
"connection": {
f"A_{i+1}": {
"a": 0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": time_step_length
}
},
"location": [2 + 3 * i, 1]
},
f"D_{i}": {
"connection": {
f"A_{i+1}": {
"a": 0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": time_step_length
}
},
"location": [2 + 3 * i, -1]
}
})
i += 1
graph_dict[f"A_{i}"] = {
"connection": {
"END": {
"a": 0,
"b": 1.0,
"capacity": capacity,
"free_flow_travel_time": time_step_length
}
},
"location": [0 + 3 * i, 0]
}
graph_dict["END"] = {"connection": {}, "location": [1 + 3 * i, 0]}
time_horizon = int(3.0 * (num_network_in_series + 1) / time_step_length)
destination = f"A_{i}->END"
adjacency_list = {
key: list(value["connection"].keys())
for key, value in graph_dict.items()
}
bpr_a_coefficient = {}
bpr_b_coefficient = {}
capacity = {}
free_flow_travel_time = {}
for o_node, value_dict in graph_dict.items():
for d_node, section_dict in value_dict["connection"].items():
road_section = dynamic_routing_utils._nodes_to_road_section(
origin=o_node, destination=d_node)
bpr_a_coefficient[road_section] = section_dict["a"]
bpr_b_coefficient[road_section] = section_dict["b"]
capacity[road_section] = section_dict["capacity"]
free_flow_travel_time[road_section] = section_dict[
"free_flow_travel_time"]
node_position = {
key: value["location"]
for key, value in graph_dict.items()
}
return dynamic_routing_utils.Network(
adjacency_list,
node_position=node_position,
bpr_a_coefficient=bpr_a_coefficient,
bpr_b_coefficient=bpr_b_coefficient,
capacity=capacity,
free_flow_travel_time=free_flow_travel_time
), origin, destination, time_horizon
