python编程原子化多智能体综合编程应用（下）

上述代码实现了基于Mesa框架的诊断智能体类，包含以下核心功能：

1. 模块化设计：通过类属性分离数据与行为，支持不同专科智能体的扩展
2. 状态管理：实现idle/processing/error等状态转换，支持任务调度
3. 诊断推理：集成机器学习模型，支持症状提取与多分类诊断
4. 错误处理：包含模型加载失败的降级策略，确保系统鲁棒性

在实际应用中，可通过Mesa的DataCollector类收集诊断准确率、处理时间等性能指标，通过BatchRunner进行多轮仿真优化智能体配置。

SPADE框架通信协议实现

SPADE框架基于XMPP协议实现智能体间通信，以下是医疗场景下通信协议的实现代码：

from spade.agent import Agent
from spade.behaviour import CyclicBehaviour, OneShotBehaviour
from spade.message import Message
from spade.template import Template
import json
import time
from datetime import datetime

class SurgeryCoordinatorAgent(Agent):
    """手术协调智能体，负责手术团队智能体的任务分配"""
    
    class TaskAssignmentBehaviour(CyclicBehaviour):
        """任务分配行为"""
        async def on_start(self):
            self.assigned_tasks = {
   
   }
            self.available_agents = []
            self.task_queue = []
        
        async def run(self):
            # 接收可用智能体状态消息
            template = Template(metadata={
   
   "performative": "status_update"})
            msg = await self.receive(template=template, timeout=10)
            
            if msg:
                agent_id = msg.sender.localpart
                status = json.loads(msg.body)["status"]
                
                # 更新可用智能体列表
                if status == "available" and agent_id not in self.available_agents:
                    self.available_agents.append(agent_id)
                    print(f"Agent {
     
     agent_id} is available")
                
                # 处理任务队列
                while self.task_queue and self.available_agents:
                    task = self.task_queue.pop(0)
                    agent_jid = f"{
     
     self.available_agents.pop(0)}@your-xmpp-server.com"
                    self.assigned_tasks[task["task_id"]] = agent_jid
                    
                    # 发送任务分配消息
                    task_msg = Message(to=agent_jid)
                    task_msg.set_metadata("performative", "assign_task")
                    task_msg.set_metadata("task_type", task["task_type"])
                    task_msg.body = json.dumps(task)
                    await self.send(task_msg)
                    print(f"Assigned task {
     
     task['task_id']} to {
     
     agent_jid}")
            
            # 接收任务完成消息
            completion_template = Template(metadata={
   
   "performative": "task_completed"})
            completion_msg = await self.receive(template=completion_template, timeout=5)
            
            if completion_msg:
                task_data = json.loads(completion_msg.body)
                task_id = task_data["task_id"]
                if task_id in self.assigned_tasks:
                    del self.assigned_tasks[task_id]
                    # 将完成任务的智能体重置为可用状态
                    agent_id = completion_msg.sender.localpart
                    if agent_id not in self.available_agents:
                        self.available_agents.append(agent_id)
                    print(f"Task {
     
     task_id} completed by {
     
     agent_id}")
    
    class TaskSubmissionBehaviour(OneShotBehaviour):
        """接收外部任务提交"""
        def __init__(self, task):
            super().__init__()
            self.task = task
        
        async def run(self):
            # 将新任务加入队列
            self.agent.behaviours[0].task_queue.append(self.task)
            print(f"Added new task to queue: {
     
     self.task['task_id']}")
    
    async def setup(self):
        print(f"Surgery Coordinator Agent started at {
     
     datetime.now()}")
        # 添加任务分配行为
        task_behaviour = self.TaskAssignmentBehaviour()
        self.add_behaviour(task_behaviour)
        # 添加任务提交行为模板
        submission_template = Template(metadata={
   
   "performative": "submit_task"})
        self.add_behaviour(self.TaskSubmissionBehaviour({
   
   }), submission_template)

class SurgicalRobotAgent(Agent):
    """手术机器人智能体"""
    
    class OperationBehaviour(CyclicBehaviour):
        """手术操作行为"""
        async def run(self):
            # 接收任务分配消息
            template = Template(metadata={
   
   "performative": "assign_task"})
            msg = await self.receive(template=template, timeout