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This commit is contained in:
J. Fernando Sánchez
2022-10-06 15:49:10 +02:00
parent 0a9c6d8b19
commit f811ee18c5
53 changed files with 856 additions and 774 deletions
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27
examples/terrorism/TerroristNetworkModel.py
View File

@@ -1,4 +1,3 @@
import random
import networkx as nx
from soil.agents import Geo, NetworkAgent, FSM, state, default_state
from soil import Environment
@@ -26,26 +25,26 @@ class TerroristSpreadModel(FSM, Geo):
self.prob_interaction = model.environment_params['prob_interaction']
if self['id'] == self.civilian.id: # Civilian
self.mean_belief = random.uniform(0.00, 0.5)
self.mean_belief = self.random.uniform(0.00, 0.5)
elif self['id'] == self.terrorist.id: # Terrorist
self.mean_belief = random.uniform(0.8, 1.00)
self.mean_belief = self.random.uniform(0.8, 1.00)
elif self['id'] == self.leader.id: # Leader
self.mean_belief = 1.00
else:
raise Exception('Invalid state id: {}'.format(self['id']))
if 'min_vulnerability' in model.environment_params:
self.vulnerability = random.uniform( model.environment_params['min_vulnerability'], model.environment_params['max_vulnerability'] )
self.vulnerability = self.random.uniform( model.environment_params['min_vulnerability'], model.environment_params['max_vulnerability'] )
else :
self.vulnerability = random.uniform( 0, model.environment_params['max_vulnerability'] )
self.vulnerability = self.random.uniform( 0, model.environment_params['max_vulnerability'] )
@state
def civilian(self):
neighbours = list(self.get_neighboring_agents(agent_type=TerroristSpreadModel))
neighbours = list(self.get_neighboring_agents(agent_class=TerroristSpreadModel))
if len(neighbours) > 0:
# Only interact with some of the neighbors
interactions = list(n for n in neighbours if random.random() <= self.prob_interaction)
interactions = list(n for n in neighbours if self.random.random() <= self.prob_interaction)
influence = sum( self.degree(i) for i in interactions )
mean_belief = sum( i.mean_belief * self.degree(i) / influence for i in interactions )
mean_belief = mean_belief * self.information_spread_intensity + self.mean_belief * ( 1 - self.information_spread_intensity )
@@ -64,7 +63,7 @@ class TerroristSpreadModel(FSM, Geo):
@state
def terrorist(self):
neighbours = self.get_agents(state_id=[self.terrorist.id, self.leader.id],
agent_type=TerroristSpreadModel,
agent_class=TerroristSpreadModel,
limit_neighbors=True)
if len(neighbours) > 0:
influence = sum( self.degree(n) for n in neighbours )
@@ -103,7 +102,7 @@ class TrainingAreaModel(FSM, Geo):
@default_state
@state
def terrorist(self):
for neighbour in self.get_neighboring_agents(agent_type=TerroristSpreadModel):
for neighbour in self.get_neighboring_agents(agent_class=TerroristSpreadModel):
if neighbour.vulnerability > self.min_vulnerability:
neighbour.vulnerability = neighbour.vulnerability ** ( 1 - self.training_influence )
@@ -129,7 +128,7 @@ class HavenModel(FSM, Geo):
self.max_vulnerability = model.environment_params['max_vulnerability']
def get_occupants(self, **kwargs):
return self.get_neighboring_agents(agent_type=TerroristSpreadModel, **kwargs)
return self.get_neighboring_agents(agent_class=TerroristSpreadModel, **kwargs)
@state
def civilian(self):
@@ -182,15 +181,15 @@ class TerroristNetworkModel(TerroristSpreadModel):
def update_relationships(self):
if self.count_neighboring_agents(state_id=self.civilian.id) == 0:
close_ups = set(self.geo_search(radius=self.vision_range, agent_type=TerroristNetworkModel))
step_neighbours = set(self.ego_search(self.sphere_influence, agent_type=TerroristNetworkModel, center=False))
neighbours = set(agent.id for agent in self.get_neighboring_agents(agent_type=TerroristNetworkModel))
close_ups = set(self.geo_search(radius=self.vision_range, agent_class=TerroristNetworkModel))
step_neighbours = set(self.ego_search(self.sphere_influence, agent_class=TerroristNetworkModel, center=False))
neighbours = set(agent.id for agent in self.get_neighboring_agents(agent_class=TerroristNetworkModel))
search = (close_ups | step_neighbours) - neighbours
for agent in self.get_agents(search):
social_distance = 1 / self.shortest_path_length(agent.id)
spatial_proximity = ( 1 - self.get_distance(agent.id) )
prob_new_interaction = self.weight_social_distance * social_distance + self.weight_link_distance * spatial_proximity
if agent['id'] == agent.civilian.id and random.random() < prob_new_interaction:
if agent['id'] == agent.civilian.id and self.random.random() < prob_new_interaction:
self.add_edge(agent)
break

8
examples/terrorism/TerroristNetworkModel.yml
View File

@@ -8,19 +8,19 @@ network_params:
# theta: 20
n: 100
network_agents:
- agent_type: TerroristNetworkModel.TerroristNetworkModel
- agent_class: TerroristNetworkModel.TerroristNetworkModel
weight: 0.8
state:
id: civilian # Civilians
- agent_type: TerroristNetworkModel.TerroristNetworkModel
- agent_class: TerroristNetworkModel.TerroristNetworkModel
weight: 0.1
state:
id: leader # Leaders
- agent_type: TerroristNetworkModel.TrainingAreaModel
- agent_class: TerroristNetworkModel.TrainingAreaModel
weight: 0.05
state:
id: terrorist # Terrorism
- agent_type: TerroristNetworkModel.HavenModel
- agent_class: TerroristNetworkModel.HavenModel
weight: 0.05
state:
id: civilian # Civilian