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：
- 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
- 状态管理：实现idle/processing/error等状态转换，支持任务调度
- 诊断推理：集成机器学习模型，支持症状提取与多分类诊断
- 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 datetimeclass 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.localpartstatus = 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.localpartif 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 = taskasync 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