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mesa/agent.py

@@ -69,8 +69,8 @@ def __init__(self, model: Model, *args, **kwargs) -> None:
         self.model.register_agent(self)
         # Private attribute to track parent agent if metaagents are created
         # Uses name mangling to prevent name clashes
-        self.__metaagent = None # Currently restricted to one parent agent
-        
+        self.__metaagent = None  # Currently restricted to one parent agent
+
     def remove(self) -> None:
         """Remove and delete the agent from the model.
 
@@ -135,9 +135,13 @@ def __getitem__(self, i):
             agent = cls(model, *instance_args, **instance_kwargs)
             agents.append(agent)
         return AgentSet(agents, random=model.random)
-
-    def create_metaagent(self, new_agent_class: str, agents: Iterable[Agent], **unique_attributes_functions) -> None:
 
+    def create_metaagent(
+        self,
+        new_agent_class: str,
+        agents: Iterable[Agent],
+        **unique_attributes_functions,
+    ) -> None:
         """Dynamically create a new meta-agent class and instantiate agents in that class.
 
         Args:
@@ -172,63 +176,74 @@ def create_metaagent(self, new_agent_class: str, agents: Iterable[Agent], **uniq
         def update_agents_metaagent(agents, metaagent):
             for agent in agents:
                 agent._Agent__metaagent = metaagent
-  
+
         # Path 1 - Add agents to existing meta-agent
         subagents = [agent for agent in agents if agent._Agent__metaagent is not None]
-        
+
         if len(subagents) > 0:
-            if len(subagents) == 1: 
+            if len(subagents) == 1:
                 # Update metaagents agent set with new agents
                 subagents[0]._Agent__metaagent.agents.update(agents)
                 # Update subagents with metaagent
                 update_agents_metaagent(agents, subagents[0]._Agent__metaagent)
-            else: 
+            else:
                 # If there are multiple subagents, one is chosen at random to be the parent metaagent
                 subagent = self.random.choice(subagents)
                 # Remove agent who are already part of metaagent
                 agents = set(agents) - set(subagents)
                 subagent._Agent__metaagent.agents.update(agents)
                 update_agents_metaagent(agents, subagent._Agent__metaagent)
                 # TODO: Add way for user to add function to specify how agents join metaagent
-                    
-        else:      
+
+        else:
             # Path 2 - Create a new instance of an exsiting meta-agent class
-            agent_class = next((agent_type for agent_type in self.model.agent_types if agent_type.__name__ == new_agent_class), None)
+            agent_class = next(
+                (
+                    agent_type
+                    for agent_type in self.model.agent_types
+                    if agent_type.__name__ == new_agent_class
+                ),
+                None,
+            )
             if agent_class:
                 # Create an instance of the meta-agent class
-                meta_agent_instance = agent_class(self.model, **unique_attributes_functions)
+                meta_agent_instance = agent_class(
+                    self.model, **unique_attributes_functions
+                )
                 # Add agents to meta-agent instance
                 meta_agent_instance.agents = agents
                 # Update subagents Agent.__metaagent attribute
-                update_agents_metaagent(agents, meta_agent_instance)  
+                update_agents_metaagent(agents, meta_agent_instance)
                 # Register the new meta-agent instance
                 self.model.register_agent(meta_agent_instance)
 
-                return meta_agent_instance 
-                
+                return meta_agent_instance
+
             # Path 3 - Create a new meta-agent class
-            else: 
+            else:
                 # Get agent types of subagents to create the new meta-agent class
-                agent_types = tuple(set((type(agent) for agent in agents)))
+                agent_types = tuple({type(agent) for agent in agents})
 
                 meta_agent_class = type(
                     new_agent_class,
                     agent_types,
                     {
                         "unique_id": None,
-                        "agents": agents, 
-                    }
+                        "agents": agents,
+                    },
                 )
-                
+
                 # Create an instance of the meta-agent class
-                meta_agent_instance = meta_agent_class(self.model, **unique_attributes_functions)
+                meta_agent_instance = meta_agent_class(
+                    self.model, **unique_attributes_functions
+                )
                 # Register the new meta-agent instance
                 self.model.register_agent(meta_agent_instance)
                 # Update subagents Agent.__metaagent attribute
-                update_agents_metaagent(agents, meta_agent_instance) 
+                update_agents_metaagent(agents, meta_agent_instance)
+
+                return meta_agent_instance
 
-                return meta_agent_instance  
-
     @property
     def random(self) -> Random:
         """Return a seeded stdlib rng."""

mesa/examples/basic/alliance_formation_model/Readme.md

@@ -2,13 +2,13 @@
 
 ## Summary
 
-This model demonstrates Mesa's ability to dynamically create new classes of agents that are composed of existing agents. These meta-agents  inherits functions and attributes from their sub-agents and users can specify new functionality or attributes they want the meta agent to have. For example, if a user is doing a factory simulation with autonomous systems, each major component of that system can be a sub-agent of the overall robot agent. Or, if someone is doing a simulation of an organization, individuals can be part of different organizational units that are working for some purpose. 
+This model demonstrates Mesa's ability to dynamically create new classes of agents that are composed of existing agents. These meta-agents  inherits functions and attributes from their sub-agents and users can specify new functionality or attributes they want the meta agent to have. For example, if a user is doing a factory simulation with autonomous systems, each major component of that system can be a sub-agent of the overall robot agent. Or, if someone is doing a simulation of an organization, individuals can be part of different organizational units that are working for some purpose.
 
-To provide a simple demonstration of this capability is an alliance formation model. 
+To provide a simple demonstration of this capability is an alliance formation model.
 
-In this simulation n agents are created, who have two attributes (1) power and (2) preference. Each attribute is a number between 0 and 1 over a gaussian distribution. Agents then randomly select other agents and use the [bilateral shapley value](https://en.wikipedia.org/wiki/Shapley_value) to determine if they should form an alliance. If the expected utility support an alliances, the agent creates a meta-agent. Subsequent steps may add agents to the meta-agent, create new instances of similar hierarchy, or create a new hierarchy level where meta-agents form an alliance of meta-agents. In this visualization of this model a new meta-agent hierarchy will be a larger node and a new color.   
+In this simulation n agents are created, who have two attributes (1) power and (2) preference. Each attribute is a number between 0 and 1 over a gaussian distribution. Agents then randomly select other agents and use the [bilateral shapley value](https://en.wikipedia.org/wiki/Shapley_value) to determine if they should form an alliance. If the expected utility support an alliances, the agent creates a meta-agent. Subsequent steps may add agents to the meta-agent, create new instances of similar hierarchy, or create a new hierarchy level where meta-agents form an alliance of meta-agents. In this visualization of this model a new meta-agent hierarchy will be a larger node and a new color.
 
-In its current configuration, agents being part of multiple meta-agents is not supported 
+In its current configuration, agents being part of multiple meta-agents is not supported
 
 ## Installation
 
@@ -36,6 +36,6 @@ To run the model interactively, in this directory, run the following command
 The full tutorial describing how the model is built can be found at:
 https://mesa.readthedocs.io/en/latest/tutorials/intro_tutorial.html
 
-An example of the bilateral shapley value in another model: 
+An example of the bilateral shapley value in another model:
 [Techno-Social Energy Infrastructure Siting: Sustainable Energy Modeling Programming (SEMPro)](https://www.jasss.org/16/3/6.html)
 

mesa/examples/basic/alliance_formation_model/agent.py

@@ -1,58 +1,68 @@
 import mesa
 
+
 def calculate_shapley_value(self, other_agent):
-        """
-        Calculate the Shapley value of the two agents
-        """
-        other_agent.hierarchy = other_agent.hierarchy
-        self.hierarchy = self.hierarchy
-        new_position = 1-abs(self.position - other_agent.position)
-        potential_utility = (self.power+other_agent.power)*1.1 * new_position
-        value_me = 0.5 * self.power + 0.5 * (potential_utility - other_agent.power)
-        value_other = 0.5 * other_agent.power + 0.5 * (potential_utility - self.power)
-
-
-        # Determine ig there is value in the alliance
-        if value_me > self.power and value_other > other_agent.power:
-            if other_agent.hierarchy>self.hierarchy:
-                hierarchy = other_agent.hierarchy
-            elif other_agent.hierarchy==self.hierarchy:
-                hierarchy = self.hierarchy+1
-            else:
-                hierarchy = self.hierarchy
-
-            return (potential_utility, new_position, hierarchy)
+    """
+    Calculate the Shapley value of the two agents
+    """
+    other_agent.hierarchy = other_agent.hierarchy
+    self.hierarchy = self.hierarchy
+    new_position = 1 - abs(self.position - other_agent.position)
+    potential_utility = (self.power + other_agent.power) * 1.1 * new_position
+    value_me = 0.5 * self.power + 0.5 * (potential_utility - other_agent.power)
+    value_other = 0.5 * other_agent.power + 0.5 * (potential_utility - self.power)
+
+    # Determine ig there is value in the alliance
+    if value_me > self.power and value_other > other_agent.power:
+        if other_agent.hierarchy > self.hierarchy:
+            hierarchy = other_agent.hierarchy
+        elif other_agent.hierarchy == self.hierarchy:
+            hierarchy = self.hierarchy + 1
         else:
-            return None
+            hierarchy = self.hierarchy
+
+        return (potential_utility, new_position, hierarchy)
+    else:
+        return None
+
 
 class alliance_agent(mesa.Agent):
     """
     Agent has three attirbutes power (float), position (float) and hierarchy (int)
-    
+
     """
+
     def __init__(self, model, power, position, hierarchy=0):
         super().__init__(model)
         self.power = power
         self.position = position
         self.hierarchy = hierarchy
 
-
     def form_alliance(self):
         # Randomly select another agent of the same type
-        other_agents = [agent for agent in self.model.agents_by_type[type(self)] if agent != self]      
-
+        other_agents = [
+            agent for agent in self.model.agents_by_type[type(self)] if agent != self
+        ]
+
         # Determine if there is a beneficial alliance
-        if other_agents: 
+        if other_agents:
             other_agent = self.random.choice(other_agents)
             shapley_value = calculate_shapley_value(self, other_agent)
             if shapley_value:
                 class_name = f"MetaAgentHierarchy{shapley_value[2]}"
-                meta = self.create_metaagent(class_name, {other_agent, self}, hierarchy=shapley_value[2], 
-                                             power=shapley_value[0],position=shapley_value[1])
-
+                meta = self.create_metaagent(
+                    class_name,
+                    {other_agent, self},
+                    hierarchy=shapley_value[2],
+                    power=shapley_value[0],
+                    position=shapley_value[1],
+                )
+
                 # Update the network if a new meta agent instance created
-                if meta: 
-                    self.model.network.add_node(meta.unique_id, size =(meta.hierarchy+1)*200) 
-                    self.model.new_agents=True
+                if meta:
+                    self.model.network.add_node(
+                        meta.unique_id, size=(meta.hierarchy + 1) * 200
+                    )
+                    self.model.new_agents = True
                 else:
-                    self.model.new_agents=False
+                    self.model.new_agents = False

mesa/examples/basic/alliance_formation_model/app.py

@@ -1,16 +1,16 @@
-import networkx as nx
 import matplotlib.pyplot as plt
+import networkx as nx
+import solara
 from matplotlib.figure import Figure
+
 from mesa.examples.basic.alliance_formation.model import alliance_model
-import solara
 from mesa.mesa_logging import DEBUG, log_to_stderr
+from mesa.visualization import SolaraViz
 from mesa.visualization.utils import update_counter
-from mesa.visualization import (SolaraViz)
 
 log_to_stderr(DEBUG)
 
 
-
 model_params = {
     "seed": {
         "type": "InputText",
@@ -33,27 +33,31 @@
 # You can also author your own visualization elements, which can also be functions
 # that receive the model instance and return a valid solara component.
 
+
 @solara.component
 def plot_network(model):
-    update_counter.get()     
+    update_counter.get()
     G = model.network
     pos = nx.spring_layout(G)
     fig = Figure()
     ax = fig.subplots()
     labels = {agent.unique_id: agent.unique_id for agent in model.agents}
-    node_sizes = [G.nodes[node]['size'] for node in G.nodes]
-    node_colors = [G.nodes[node]['size'] for node in G.nodes()]
+    node_sizes = [G.nodes[node]["size"] for node in G.nodes]
+    node_colors = [G.nodes[node]["size"] for node in G.nodes()]
+
+    nx.draw(
+        G,
+        pos,
+        node_size=node_sizes,
+        node_color=node_colors,
+        cmap=plt.cm.coolwarm,
+        labels=labels,
+        ax=ax,
+    )
 
-    nx.draw(G, 
-            pos,
-            node_size = node_sizes,
-            node_color = node_colors,
-            cmap=plt.cm.coolwarm,
-            labels=labels,
-            ax=ax)
-
     solara.FigureMatplotlib(fig)
 
+
 # Create initial model instance
 model = alliance_model(50)
 

mesa/examples/basic/alliance_formation_model/model.py

@@ -1,15 +1,16 @@
+import networkx as nx
 import numpy as np
-import mesa
 from agent import alliance_agent
-import networkx as nx
+
+import mesa
+
 
 class alliance_model(mesa.Model):
     def __init__(self, n=50, mean=0.5, std_dev=0.1, seed=42):
         super().__init__(seed=seed)
         self.population = n
         self.network = nx.Graph()  # Initialize the network
         self.datacollector = mesa.DataCollector(model_reporters={"Network": "network"})
-
 
         # Create Agents
         power = np.random.normal(mean, std_dev, n)
@@ -22,14 +23,15 @@ def __init__(self, n=50, mean=0.5, std_dev=0.1, seed=42):
 
     def add_link(self, metaagent, agents):
         for agent in agents:
-            self.network.add_edge(metaagent.unique_id, agent.unique_id) 
+            self.network.add_edge(metaagent.unique_id, agent.unique_id)
 
     def step(self):
-        for agent_class in list(self.agent_types):  # Convert to list to avoid modification during iteration
+        for agent_class in list(
+            self.agent_types
+        ):  # Convert to list to avoid modification during iteration
             self.agents_by_type[agent_class].shuffle_do("form_alliance")
 
             # Update graph
             if agent_class is not alliance_agent:
                 for metaagent in self.agents_by_type[agent_class]:
-                    self.add_link(metaagent, metaagent.agents)  
-
+                    self.add_link(metaagent, metaagent.agents)

tests/test_agent.py

@@ -691,6 +691,7 @@ def __init__(self, model, power, position, hierarchy=0):
         self.position = position
         self.hierarchy = hierarchy
 
+
 def test_create_metaagent():
     model = Model()
     agent1 = TestMetaAgent(model, power=0.5, position=0.5)
@@ -699,21 +700,27 @@ def test_create_metaagent():
     agent4 = TestMetaAgent(model, power=0.8, position=0.8)
 
     # Test creating a new meta-agent class
-    meta = agent1.create_metaagent("MetaAgentClass1", {agent1, agent2}, power=1.1, position=0.55, hierarchy=1)
+    meta = agent1.create_metaagent(
+        "MetaAgentClass1", {agent1, agent2}, power=1.1, position=0.55, hierarchy=1
+    )
     assert len(model.agent_types) == 2
     assert len(model.agents) == 5
     assert meta.power == 1.1
     assert meta.position == 0.55
     assert meta.hierarchy == 1
 
     # Test adding agents to an existing meta-agent
-    agent1.create_metaagent("MetaAgentClass1", {agent3, agent2}, power=1.8, position=0.65, hierarchy=1)
+    agent1.create_metaagent(
+        "MetaAgentClass1", {agent3, agent2}, power=1.8, position=0.65, hierarchy=1
+    )
     assert len(model.agent_types) == 2
     assert len(model.agents) == 5
     assert len(meta.agents) == 3
 
     # Test creating a new instance of an existing meta-agent class
-    meta2 = agent4.create_metaagent("MetaAgentClass2", {agent4}, power=0.8, position=0.8, hierarchy=2)
+    meta2 = agent4.create_metaagent(
+        "MetaAgentClass2", {agent4}, power=0.8, position=0.8, hierarchy=2
+    )
     assert len(model.agent_types) == 3
     assert len(model.agents) == 6
     assert meta2.power == 0.8