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Subnet.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import math
import numpy as np
# 子网的类
class Subnet:
def __init__(self, id, subnet_agents, subnet_task_capacity):
# 基础信息
self.id = id
self.subnet_agents = subnet_agents
self.agents_num = len(subnet_agents)
self.T_load_ave = 0.0
# 任务相关
self.currentBid = {} # 第一层协商中，子网对各个任务的当前投标值
self.subnet_tasks = [] # 本子网最终确定接收的任务
self.task_capacity = subnet_task_capacity # 本子网的任务容量
# 计算子网中的平均负载
def calculate_T_load_ave(self):
self.T_load_ave = 0.0
for agent in self.subnet_agents:
agent.calculate_T_load()
self.T_load_ave += agent.T_load
self.T_load_ave = self.T_load_ave / self.agents_num
# 确定符合agent任务喜好的任务列表
def determine_agent_Bid_list(self):
for task in self.subnet_tasks:
for agent in self.subnet_agents:
agent.P_get_destroyed[task.id] = task.threat - agent.defense # agent被摧毁的概率
if agent.P_get_destroyed[task.id] < agent.pref:
agent.Bid_list.append(task) # 将符合偏好的任务加入任务列表
agent.states[task.id] = "WAITING" # 初始化agents对该任务的投标状态为“等待（WAITING）”
# 根据子网中所有agent的相关信息大致计算子网的攻防能力
def calculate_subnet_AD_ability(self):
self.value = 0.0 # 子网价值，取值范围为[0,100]
self.attack = 0.0 # 子网攻击力，取值范围为[0,100]
self.defense = 0.0 # 子网防御力，取值范围为[0,100]
for agent in self.subnet_agents:
self.value += agent.value
self.attack += agent.attack
self.defense += agent.defense
self.value = self.value / len(self.subnet_agents)
self.attack = self.attack / len(self.subnet_agents)
self.defense = self.defense / len(self.subnet_agents)
# 根据子网的攻防能力，大致计算子网对某任务的总效能函数/投标值
def calculate_subnet_Bid(self, task):
# 计算子网的攻防能力
self.calculate_subnet_AD_ability()
# 计算执行此任务的收益价值reward
P_destroy = self.attack - task.defense # 任务目标被摧毁的概率
reward = task.value * P_destroy / 100
# 计算执行此任务的开销成本cost
P_get_destroyed = task.threat - self.defense # 子网agent被摧毁的概率
if P_get_destroyed < 0:
P_get_destroyed = 0
cost = self.value * P_get_destroyed / 100 # 因为是大致计算，所以这里省略了距离因素
# 计算执行此任务的净效能profit
profit = (reward - cost) * task.priority
# 计算对此任务的投标值
self.currentBid[task.id] = profit
# 合同网第二级协商：遍历所有子网任务，为每个任务分配一个bestAgent作为contractor
def second_layer_BID(self):
# 确定每个agent的待投标任务列表
self.determine_agent_Bid_list()
for task in self.subnet_tasks:
if task.contractor == None:
bestBid = -(math.inf)
bestAgent = None
BID_agents = []
self.calculate_T_load_ave
# A、确定参与投标的agent
for agent in self.subnet_agents:
# 判断1：如果该任务不在agent的待投标任务列表中，则退出投标
if task not in agent.Bid_list:
continue
# 判断2：如果agent任务容量已满，则退出投标
elif len(agent.contracted_list) == agent.task_capacity:
agent.states[task.id] == "DEF_REJ"
agent.currentBid[task.id] = -(math.inf)
continue
# 符合条件的待投标agent，进入投标环节
else:
# 每个agent进行一次判断，更改投标状态和计算投标值
agent.determine_states(task)
# 如果该agent的状态是“预投标（PRE_BID）”，则将其加入投标列表BID_agents
if agent.states[task.id] == "PRE_BID":
BID_agents.append(agent)
# print("agent ", agent.id, " 's state for task ", task.id, " is: ", agent.states[task.id])
# 计算投标值
agent.calculate_Bid(task, self.T_load_ave)
# print("agent ", agent.id, " 's bid for task ", task.id, " is: ", agent.currentBid[task.id])
# B、确定bestAgent
for agent in BID_agents:
if(agent.currentBid[task.id] > bestBid):
bestBid = agent.currentBid[task.id]
bestAgent = agent.id
# C、确定bestAgent的最终投标状态
if(bestAgent != None):
for agent in BID_agents:
if agent.id == bestAgent:
agent.states[task.id] = "DEF_BID" # 如果是bestAgent，则该agent中标
task.bestBid[agent.id] = bestBid
else:
agent.states[task.id] = "DEF_REJ" # 如果不是bestAgent，则该agent流标
# D、最后更新一次所有agent的状态，如果状态是DEF_BID，则确定为contractor
for agent in BID_agents:
agent.determine_states(task)