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Agents FSM
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@ -1,6 +1,6 @@
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import random
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import networkx as nx
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from soil.agents import BaseAgent, FSM, state
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from soil.agents import BaseAgent, FSM, state, default_state
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from scipy.spatial import cKDTree as KDTree
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global betweenness_centrality_global
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@ -133,7 +133,7 @@ class TerroristSpreadModel(FSM):
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return [ G.nodes()[index]['agent'] for index in nodes ]
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class TrainingAreaModel(BaseAgent):
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class TrainingAreaModel(FSM):
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"""
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Settings:
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training_influence
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@ -150,13 +150,15 @@ class TrainingAreaModel(BaseAgent):
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self.min_vulnerability = environment.environment_params['min_vulnerability']
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else: self.min_vulnerability = 0
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def step(self):
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@default_state
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@state
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def terrorist(self):
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for neighbour in self.get_neighboring_agents():
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if isinstance(neighbour, TerroristSpreadModel) and neighbour.vulnerability > self.min_vulnerability:
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neighbour.vulnerability = neighbour.vulnerability ** ( 1 - self.training_influence )
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neighbour.vulnerability = neighbour.vulnerability ** ( 1 - self.training_influence )
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class HavenModel(BaseAgent):
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class HavenModel(FSM):
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"""
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Settings:
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haven_influence
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@ -176,23 +178,22 @@ class HavenModel(BaseAgent):
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else: self.min_vulnerability = 0
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self.max_vulnerability = environment.environment_params['max_vulnerability']
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def step(self):
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civilian_haven = False
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if self.state['id'] == 0:
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for neighbour_agent in self.get_neighboring_agents():
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if isinstance(neighbour_agent, TerroristSpreadModel) and neighbour_agent['id'] == neighbor_agent.civilian.id:
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civilian_haven = True
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@state
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def civilian(self):
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for neighbour_agent in self.get_neighboring_agents():
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if isinstance(neighbour_agent, TerroristSpreadModel) and neighbour_agent['id'] == neighbour_agent.civilian.id:
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for neighbour in self.get_neighboring_agents():
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if isinstance(neighbour, TerroristSpreadModel) and neighbour.vulnerability > self.min_vulnerability:
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neighbour.vulnerability = neighbour.vulnerability * ( 1 - self.haven_influence )
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return self.civilian
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return self.terrorist
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if civilian_haven:
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self.state['id'] = 0 # Civilian Haven
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for neighbour in self.get_neighboring_agents():
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if isinstance(neighbour, TerroristSpreadModel) and neighbour.vulnerability > self.min_vulnerability:
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neighbour.vulnerability = neighbour.vulnerability * ( 1 - self.haven_influence )
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else:
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self.state['id'] = 1 # Terrorism Haven
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for neighbour in self.get_neighboring_agents():
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if isinstance(neighbour, TerroristSpreadModel) and neighbour.vulnerability < self.max_vulnerability:
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neighbour.vulnerability = neighbour.vulnerability ** ( 1 - self.haven_influence )
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@state
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def terrorist(self):
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for neighbour in self.get_neighboring_agents():
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if isinstance(neighbour, TerroristSpreadModel) and neighbour.vulnerability < self.max_vulnerability:
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neighbour.vulnerability = neighbour.vulnerability ** ( 1 - self.haven_influence )
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return self.terrorist
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class TerroristNetworkModel(TerroristSpreadModel):
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@ -1,6 +1,6 @@
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name: TerroristNetworkModel_sim
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load_module: TerroristNetworkModel
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max_time: 100
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max_time: 100
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num_trials: 1
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network_params:
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generator: random_geometric_graph
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